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Location: New York, NY (HQ); San Francisco, CA; Remote (US) Workplace: Remote ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE How we build software is changing. Designers are building tools and agents, prototyping in code, and shipping directly into the product. More people can create software than ever before. That makes design judgment more important, not less. We’re looking for a Design Systems Lead to build that judgment into the foundations of Ramp. This is not just about maintaining a component library. It’s about making it possible for designers, engineers, and agents to build experiences that look, feel, and work like Ramp—without a designer driving every decision or the design systems team reviewing every change. You’re a designer first, with the technical depth to guide architecture and get into the code. You have exceptional taste and strong opinions about typography, hierarchy, interaction, and motion. Just as importantly, you know how to turn that judgment into patterns, tools, and guidance that make everyone else’s work better. You’re deeply curious about AI and already using it to change how you work. You build, experiment, inspect the results, and push past the demo. You can imagine a different way of building software—and lead a team toward it. This role is for you if you’re excited by: - Making great design reproducible. Raise the quality of Ramp’s product and encode what makes it good, so people and agents can produce coherent, usable experiences by default. The system should make excellent work easier, not make every experience look the same. - Reimagining what a design system can be. Build beyond components and tokens into composition, interaction patterns, agent guidance, and evaluations. Connect exploration and production so the fastest way to build is also a path to great quality. - Leading a team that multiplies everyone else’s impact. Create clear direction, ambitious goals, and a caring yet demanding environment. Inspire curiosity, develop people, and stay close enough to the work to help make it exceptional. The opportunity is to raise the floor for everyone building at Ramp, while giving designers more room to make the most important experiences extraordinary. WHAT YOU'LL DO - Lead and develop the design systems team. Set clear priorities, ownership, and goals. Give direct, timely feedback, hold people accountable, and help them do the best work of their careers. - Own the system’s vision and direction. Decide what to preserve, evolve, simplify, or replace based on what builders and customers need. Turn that direction into focused work the team can deliver. - Elevate Ramp’s visual and interaction design. Raise the bar for typography, hierarchy, density, motion, responsive behavior, accessibility, and the states beyond the happy path. - Make design judgment usable by people and agents. Translate principles into reusable patterns, reference experiences, composition rules, and guidance that produce better work without you in the room. - Guide technical architecture with engineering. Shape everything from components and tokens to how agents discover guidance, compose interfaces, and check their work. Make sound tradeoffs between flexibility, coherence, performance, and ease of use. - Stay hands-on. Build prototypes, work in code, and get into implementation details to test ideas, unblock the team, and understand where the system breaks down. - Define and measure quality. Build repeatable evaluations grounded in real tasks. Measure whether builders can ship better work faster, with less rework—not just whether they use the tools. - Improve the path from idea to shipped experience. Partner with engineering and AI teams on workflows that support fast exploration, useful iteration, and appropriate production safeguards. - Earn adoption. Work alongside product teams, listen closely, teach through examples, and turn recurring questions and exceptions into improvements to the system. - Keep the team moving forward. Experiment as models and tools evolve, share what you learn, and change direction when the evidence calls for it. WHAT YOU NEED - Experience leading and developing strong design or design engineering teams, with a track record of setting direction and delivering meaningful outcomes. - Exceptional visual and interaction design skills. Your work shows a clear point of view, attention to detail, and an ability to make complex experiences feel simple. - Deep systems thinking and experience building systems that other teams actually adopt. You can show how your work improved both their speed and the quality of what shipped. - Strong technical fluency. You can prototype and build in code, understand front-end architecture, and work through implementation tradeoffs with engineers—not just hand off specifications. - Active, hands-on use of AI in your design and building workflow. You understand where it helps, where it fails, and how to improve its output rather than accept it. - Experience turning design principles into practical guidance, reusable patterns, and quality checks that work at scale. - Strong product judgment and a habit of staying close to the people using what you build. You connect system decisions to real workflows and customer outcomes. - The ability to create clarity in ambiguity, make decisions, give difficult feedback, and maintain momentum without losing the quality bar. - Curiosity that borders on obsession about how AI changes software and how we build it—and the ability to ignite that curiosity in others. NICE TO HAVES - Experience building agent-usable design guidance, generation workflows, or evaluations for design quality. - Experience building developer or designer tools that became part of other teams’ daily workflow. - Experience leading a major design-system migration or company-wide change in how teams build. - Experience evolving a system across platforms or connecting product and brand experiences. - Founder or early-stage startup experience. BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: Remote - US Sr. Developer Relations Manager Backblaze — Remote, US Compensation: $172,000–$215,000 base + equity About Backblaze Backblaze is the object storage layer for AI and data-intensive workloads, fueling customer success with cloud storage purpose-built for scalable performance and economics. We make customers unstoppable by solving their toughest storage challenges. Today we manage nearly 6 billion gigabytes of data for 500K+ customers across 175+ countries with fast growth among Neoclouds, GenAI companies, and companies reliant on data–heavy workloads. Developers are at the center of our next chapter, and we're serious about earning their trust. About the Role Developer relations is evolving quickly. Coding agents, informed by reference architectures and machine-readable documentation, are increasingly making integration decisions on behalf of developers. And trust, transparency, and human interaction are more important than ever as open source ideals and corporate agendas are weirdly attacked, limited, or promoted by unexpected sources and trends. Backblaze B2 Cloud storage was launched as a result of developer demand and has been committed to the developer ecosystem since day one. Today, we are seeking a leader who can help us become more present and trusted than ever before in this space, both as the storage default for agent-led projects and as a leading source of support, inspiration, and enablement for developers who need storage for whatever they’re building. As Sr. Developer Relations Manager, you'll work across a strong set of existing assets — a mature docs team, an engineering team focused on AI ecosystem integrations, our Flamethrower Startup Program, a content org, and an outward-facing SE team — and coordinate their outputs into a coherent, credible developer presence that earns mindshare where it matters most. This is a program-defining role for someone who thinks in systems, works backwards from adoption goals, knows how to make a company technically credible with developers who haven't heard of it yet, and is comfortable both channeling and being the face of developer relationships at Backblaze. What You'll Own Developer Presence in the Agentic Stack The primary goal of this role is to ensure Backblaze B2 is the best storage layer for developers and for their agents. That means understanding how AI coders discover and evaluate infrastructure tools today: through MCP servers, coding agent contexts, reference architectures, SDKs, and machine-readable documentation. You'll work with the internal AI team to define what "agent-ready" means for Backblaze and drive execution against it across engineering, docs, and content. Cross-Functional Coordination This role starts as an individual contributor, but you'll have real influence over a strong set of resources: an engineering team building integrations into AI tooling (MLFlow, ComfyUI, Hugging Face, popular agent frameworks), a docs team that can be directed toward structured, agent-consumable formats, a content org that can amplify what you build, and an SE team that can extend your enablement work, among a number of others at the company. Your job is to coordinate these teams around a unified developer strategy, keep that strategy moving, and share its outputs with the broader world. Community and Ecosystem Developers trust other developers. You'll underscore Backblaze's credibility in the communities where AI builders live: GitHub, Discord, open source projects, developer events, and the growing ecosystem of AI infrastructure tooling. You'll elevate internal technical voices, use their expertise to build your own thought leadership in the space, and partner with ecosystem players, and show up in a way that is earned, not marketed. Critically, you should have a presence in this community before coming to the role. Developer Feedback Loop You'll maintain a tight feedback loop from the developer community back to product and engineering — surfacing adoption friction, unmet integration needs, and emerging patterns worth prioritizing. The Flamethrower Startup Program gives you direct access to early-stage builders who can serve as signal-rich canaries for what's working and what isn't. Metrics and Program Accountability You'll define what success looks like — developer signups, activation rates, B2 adoption in AI frameworks, community engagement, content reach — and own progress against it. We're building this program to drive real revenue, and you'll be expected to connect the dots between awareness and conversion. Success in this role opens the door to bringing on, or from elsewhere in the company, developer resources to grow the program. What We're Looking For Meaningful DevRel, developer marketing, or developer experience leadership at a cloud infrastructure, open source, or AI tooling company. You've built or significantly grown a developer program, not just contributed to one. Understand how agentic workflows are reshaping how developers discover and integrate infrastructure tools — and you have opinions about what that means for DevRel strategy. Technically credible. You can read a codebase, evaluate an SDK, write a working integration, and have a real conversation with an engineer about tradeoffs. You don't need to be a full-time SWE, but you need to have been one, or close to it. Worked, or started, without a large team. You know how to amplify yourself through cross-functional relationships, external partners, and community rather than headcount. Strong communicator — to developers externally and to leadership internally. You can write a crisp technical tutorial and a clear exec summary with equal ease. Existing presence in developer communities. A following, conference talks, open source contributions, a technical blog — some signal that developers pay attention when you show up. Strong plus: Direct experience with model training, data processing or generative media Familiarity with how coding agents (Claude Code, Cursor, Copilot, etc.) surface and recommend infrastructure tools Experience working with or building on top of open source frameworks in the AI/ML ecosystem (MLflow, DVC, Ray Data, WebDataset, and MosaicML Streaming) Prior experience running or contributing to a startup/developer program (accelerator, cohort model, or similar) What You'll Have to Work With You won't be starting from scratch. You'll work closely with: A mature, capable docs team that can be directed toward agent-consumable documentation formats and structured reference content A strong engineering team dedicated to integrating Backblaze into the AI tooling ecosystem — building connectors, working on external integrations, and driving internal product improvements for developer use cases Flamethrower , our startup program, which is already generating community energy and early-adopter signal among AI builders An outward-facing solutions engineering team that can extend your enablement work with hands-on technical support A content org that can help produce and amplify developer-facing assets Active strategic work from Rawkode Academy laying the DevRel foundation: audit, persona validation, content models, and engagement strategy Why This Matters Now Developers are making storage decisions earlier in the stack than ever before — often before they've spoken to a salesperson, often through a coding agent recommending a reference architecture. Backblaze has the right product, the right price point, and a growing engineering investment behind this motion. What we need is the person who can translate that into developer conviction at scale. The window to establish Backblaze as the default AI storage layer is open now. This role exists to make sure we don't miss it. Backblaze Perks Healthcare for family, including dental and vision Competitive compensation and 401K RSU grants for full-time employees ESPP program Flexible vacation policy Maternity & paternity leave MacBook Pro plus a generous workstation stipend Childcare bonus Fertility treatment and support Learning & development program Commuter benefits Culture that supports a healthy work-life balance Pay Transparency To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. Final offer amounts are determined by multiple factors including candidate location, skills, depth of work experience, and relevant licenses/credentials. The expected salary range for this role is $172,000 - $215,000 plus 20% target annual bonus and RSUs. At Backblaze, we value being fair and good to our customers, partners, and employees. Diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We are proud to be an Equal Opportunity Employer. Backblaze is proud to be an Equal Opportunity Employer. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education.

Location: Parkland, USA Appodeal is a dynamic US-based product company with a truly global presence. We have offices in Warsaw, Barcelona and Parkland (FL), along with remote team members located around the world. Our company thrives on diversity, collaboration, and innovation, making us a leader in the mobile app monetization space. Why Appodeal? At Appodeal, we’re more than just a company—we’re a team united by a common mission: Help people discover and grow their talents through products that enable successful mobile app businesses! We take pride in our cutting-edge product and our internationally dispersed team of talented professionals. Here’s what we value, and what we hope you do too: Seek the Truth and Say It with Care: We find the truth together, and nobody owns it, the CEO included. Stories, perspectives and beliefs can be personal. Facts can’t. Leverage Data to Build Product: Our decisions start from data. We build systems rather than one-off tasks, use AI agents in our daily work and automate whatever is manual. When numbers don’t match, we fix them. We Work Together to Serve Others: No closed doors between teams. We share what we learn and win as one company first. Insist on Higher Standards: We don’t settle for “good enough”. We question it and push for better. Passionate Curiosity Fuels Perseverance: We ask “why”, take on ambiguous problems and keep going when they get hard. Lean Startup Mentality: Start Small, Iterate Quickly: Think big, ship an MVP first and learn fast. No big-bang releases. Ownership and Accountability: We work in small squads so each team owns its result end to end and has the freedom to get there. Go deep in your craft and wide enough to own the whole outcome. Escalate blockers early, admit mistakes, fix the damage and learn. About the Role We're hiring an Office Manager to join our Parkland office. As an Office Manager you keep this place running: the daily condition of every room and system, the vendors and the landlord, food and supplies, the equipment and screens, the logistics of every visit, and the calendar of events that gives the office its social life. There is also a building job inside this one - nothing here is automated yet. There is no tool that reorders supplies, chases vendors, reminds you about birthdays, restarts the screens or passes the team's feedback to our chef, and the office's own reporting is put together by hand. Setting that up is part of the role, and a good place to start is an automatic count of the things that were not caught in time. What stays with a person is everything that needs someone in the building: walking the space before the day begins, being there when the AC technician arrives, setting up a room, welcoming a visitor, noticing the thing no system is watching. If you enjoy shaping things that are still taking form, there is plenty of room here. Key Responsibilities 1. Daily condition of the office Walk the building every morning before core hours against a documented checklist: every room, plus electrical, Wi-Fi and technology, plumbing, access and air conditioning. Turn anything failing into a task for the handyman or a vendor ticket the same morning. Keep the kitchen, bathrooms, gym and outdoor areas to our standard, with a little buffer on the items people notice straight away. 2. Vendors, landlord and repairs Choose and manage the vendors the office works with: air conditioning, pool, landscaping, electrical, gate, security, cleaning and grounds. See every ticket through to a close: an owner, a date, someone on site for the visit, a check that the work was done well, and the invoice filed. Hold the relationship with the landlord for repairs and payments, and support a lease renewal or a possible office move. 3. Equipment and technology Own the state of the office equipment: screens and dashboards, the video portal, meeting-room AV, and access credentials. Work closely with the on-site handyman, who is hands-on with much of the technical setup and systems, while remaining the person who owns the overall picture. 4. Food, kitchen and supplies Send meal counts to the office chef on schedule and adjust them as the week changes. Order supplies for the kitchen, bathrooms, gym, laundry and printing, and keep stock ahead of demand. Choose office food suppliers and catering, including finding alternatives when the team's feedback points that way. 5. Leadership sessions, QBRs and visitors Run the ground logistics for every visit: rooms, AV, meals through the day, arrivals and access. Get in touch with each visitor beforehand with the address, hotel options, timings and what to expect on site. Put the whole logistics plan in the calendars of the visitors. 6. Team calendar, events and culture Plan the year ahead: birthdays, seasonal holidays and office decoration, Friendsgiving, Christmas and gift exchanges, with the lead times each of them needs. Organize team activities people actually want — wakeboarding, cooking classes, concerts and similar — and company volunteering, where employees give their time. Partner with the office managers in Poland and Spain on shared events and practices. 7. Automation and measurement Set up and run the office's own reporting, including a count of the issues that were not caught in time, produced automatically rather than by hand. Automate the repetitive coordination: reordering, reminders, vendor scheduling, equipment checks, and feedback between the team and the chef. Keep the office standard, vendor register and documentation up-to-date in Confluence. 8. Budget and spend Track office spend, keep purchases within agreed limits, and flag where the office is overpaying. Act straight away in an emergency within an agreed limit, and route larger commitments through your manager. What We're Looking For Three or more years in office management, facilities, executive support or hospitality , with direct experience running a site or a residence to a high standard. Evidence of having owned a place end to end — a vendor tracker or system you built, a budget you held, an event you ran from start to finish for senior people. Hospitality sense and exceptional attention to detail. You look at a catered table and see that it needs plates, napkins, serving spoons in each dish, drinks and ice, without anyone mentioning it. Real comfort with AI tools . Practical hands-on use of AI tools in office, facilities or executive-support work: which specific workflows you improved, what results it produced, and how you checked the output was right. Comfort working with numbers and dashboards. You can pull together spend and office data, check it, and explain simply what it shows to someone who has not looked at it. Follow-through without reminders. You close loops nobody is watching. Proactive planning in weeks and months, not days. Clear, warm communication, including with senior people , and good judgement about when not to interrupt. Fluent English , written and spoken. Confident with Google Workspace, Zoom, office dashboards, password managers, Atlassian (Jira and Confluence) and meeting tools such as Fellow — or able to pick them up quickly. Based in or willing to relocate to the Parkland area, and available for occasional evening and weekend work. Nice to Have A background in luxury hospitality or private-client service. Curiosity about automation and the basics of how software and scripts work. Russian, in addition to English. Not required; the office runs in English. Experience preparing a site for severe weather, or willingness to learn it. Location and Travel Parkland, Florida -  on site in Parkland five days a week. No business travel. A driver's licence and your own car are strongly preferred. With an outstanding product and a mission that excites and inspires, Appodeal offers a unique opportunity to make an impact while being part of an amazing team. Join us and help shape the future of mobile app success!

Location: United Kingdom Workplace: Remote 1Password is growing. We’ve surpassed $500M in ARR and we’re continuing to accelerate, earning a spot on the Forbes Cloud 100 for four years in a row and teaming up with iconic partners like Oracle Red Bull Racing. About 1Password At 1Password, we’re building the foundation for a safe, productive digital future. Our mission is to unleash employee productivity without compromising security by ensuring every identity is authentic, every application sign-in is secure, and every device is trusted. We innovated the market-leading enterprise password manager and pioneered Unified Access Management, a new cybersecurity category built for the way people and AI agents work today. As one of the most loved brands in cybersecurity, we take a human-centric approach in everything from product strategy to user experience. Over 180,000 businesses, from Fortune 100 leaders to the world’s most innovative AI companies, trust 1Password to help their teams securely adopt the SaaS and AI tools they need to do their best work. If you're excited about the opportunity to contribute to the digital safety of millions, to work alongside a team of curious, driven individuals, and to solve hard problems in a fast-paced, dynamic environment, then we want to hear from you. Come join us and help shape a safer, simpler digital future. As a Senior CSM at 1Password, you own and strategically manage a portfolio of customers – driving value realization, revenue retention, and expansion outcomes that consistently exceed expectations. You operate with full commercial autonomy: advancing expansion opportunities independently, engaging VP and C-suite stakeholders as a trusted advisor, and managing complex renewals without escalation. Beyond your own book, you raise the bar for the team through mentorship, playbook contributions, and peer enablement. How we’re using AI today Across GTM, we’re transforming the way we work with AI. We expect every seller, CSM, and team member to become a power user, using it daily to work smarter and move faster. AI is already embedded in how we operate – from real-time coaching that sharpens how we sell and interact with customers, to surfacing insights that help us anticipate needs – creating more time for meaningful customer engagement. If you’re excited to reshape how you think, make decisions, and drive growth with AI, you’ll feel right at home here. This is a remote opportunity within the UK. Note: All go-to market roles will have an in-person onboarding in Toronto. What we're looking for: - 6+ years in a customer-facing, consultative, or technical role in SaaS – Customer Success, Solutions Engineering, Technical Account Management, or IT/security leadership. - Demonstrated track record of exceeding retention, adoption, and expansion outcomes; experience recognized with performance distinction is a plus. - Proven ability to run executive business reviews with VP and C-suite stakeholders. - Background in cybersecurity, IAM, identity security, or enterprise IT preferred; former 1Password power user is a strong plus. - Strategic success planning and multi-threaded stakeholder management across a complex portfolio. - Commercial acumen: independently qualifies, advances, and documents expansion opportunities; manages negotiations without oversight. - Designs and applies AI-assisted workflows to commercial execution; documents use cases in a shareable format. - Strong Gainsight and Salesforce hygiene; consistent forecasting discipline. - Highly autonomous; manages complex accounts without requiring managerial direction. - Commercial thinker who connects customer outcomes to expansion potential naturally. - Strong executive presence – adapts messaging across technical, operational, and C-suite audiences. - Elevates teammates through knowledge sharing and informal mentorship. What you can expect: OWN AND GROW YOUR BOOK OF BUSINESS - Independently manage a portfolio of moderately to highly complex accounts – adapting success plans to each customer’s context without manager guidance. - Maintain full success plan coverage; produce documented best practices and playbooks, applied broadly across accounts with measurable KPI improvement. - Proactively identify and mitigate renewal risks; close risk CTAs with a high rate of success within defined timeframes. DRIVE ADOPTION & VALUE REALIZATION - Achieve strong Executive Sponsor attendance in EBRs across segments; EBRs are value-driven, data-backed, and consistently advance renewal confidence. - Maintain commercial intelligence across strategic accounts – budget cycles, org changes, compliance mandates, and stack rationalization. - Translate advanced 1Password capabilities into clear outcomes for VP and C-suite stakeholders; tie adoption to measurable ROI and long-term advocacy. LEAD REVENUE RETENTION & EXPANSION - Achieve strong amendment and renewal upsell win rates; proactively source and advance expansion opportunities with documented context. - Maintain forecasting hygiene with minimal blank or unmodified renewals approaching subscription end. OPERATE WITH STRATEGIC RIGOR - Manage commercial objections, renewal negotiations, and competitive conversations independently – without escalation for standard to complex scenarios. - Build and present business cases to customer champions; advance deals with enough depth to move through the pipeline with AE alignment. ACT AS A TRUSTED SECURITY ADVISOR - Deep working knowledge of the full 1Password product suite; design tailored success journeys connecting feature adoption to measurable business outcomes. - Incorporate regulatory context, breach patterns, and competitive dynamics into EBRs with confidence. - Design and share AI-assisted workflows with teammates in a replicable, documented format. COLLABORATE & ENABLE - Lead joint account planning with your AE; cited by AEs as a proactive commercial collaborator who improves deal outcomes. - Mentor Level B CSMs through call shadowing, ad hoc coaching, or onboarding support. - Lead or co-lead cross-team initiatives; contribute tools or improvements adopted by peers. MONTH 1 – ONBOARDING & FOUNDATION - Develop fluency in 1Password’s full product suite, CS methodology, and commercial motion. - By the end of Month 1, you will independently manage customer touchpoints and demonstrate clear understanding of renewal drivers across your portfolio. MONTH 3 – PORTFOLIO OWNERSHIP - Full ownership of your book with consistent EBR cadence and expansion sourcing. - By Month 3, you are meeting key performance targets and expansion leads are flowing to Sales with documented context. MONTH 6 – STRATEGIC IMPACT - Operating at full commercial autonomy; contributing to team practices and mentoring peers. - By Month 6, you are achieving top-tier customer satisfaction and recognized as a reliable commercial collaborator by your AE and cross-functional partners. UK-based roles only: The annual base salary for this role is between £73,000 GBP and £106,000 GBP, and is commission-eligible. This role is also eligible for immediate participation in 1Password's benefits program (health, dental, pension, and many others), utilization of our generous paid time off, an equity grant and, where applicable, participation in our incentive programs. At 1Password, we approach each individual's compensation with a promise of fair market value and internal equity commensurate with experience and specific skill set. This posting is for an existing vacancy. Our culture At 1Password, we prioritize collaboration, clear and transparent communication, receptiveness to feedback, and alignment with our core values: keep it simple, lead with honesty, and put people first. You’ll be part of a team that challenges the status quo, and is excited to experiment and iterate in search of the best solution. That said, 1Password is not for everyone https://blog.1password.com/inside-the-culture-powering-1passwords-next-chapter/. Our work is demanding, we strive for excellence, and the pace is fast. We need people who are keen to take on challenging problems, who seek feedback to grow, and who are driven to make an impact. If you're looking for a place where you can settle into a comfortable routine, this might not be the right fit for you. We’re looking for individuals who are proven experts in their fields, as well as those who are highly adaptable, can thrive in ambiguity and through change, are curious, and above all deliver results. How we work with AI We are committed to leveraging cutting-edge technology—including AI—to achieve our mission. We also understand that thinking critically about AI in its current forms will help us create better solutions for our customers and ourselves with its future forms, which will help us continue to close the gap between security and privacy and achieve our mission. We want team members at all levels to take the approach of actively learning AI best practices, identifying opportunities to apply AI in meaningful ways, and driving innovative solutions in their daily work. Embracing the future of AI isn't just encouraged—it's an essential part of how we will be successful at 1Password. This approach extends to our hiring process—candidates are welcome to use AI tools responsibly and thoughtfully during the application process. To us, this means we do ask that you join live interviews without using AI tools so we can get to know how you communicate, solve problems, and collaborate with others. Our approach to work We recognize the power of both in person collaboration and remote work. Some roles are designated as remote-first, with an expectation that individuals work from their homes majority of the time, while others are designated as in-office roles, with an expectation of being on-site on a regular basis. We recognize that certain roles benefit from regular, in-person connection to support collaboration, team cohesion, and customer engagement. For all roles, occasional travel may be required. This includes things like: department-wide offsites, quarterly department meetings and periodic customer events. These events are typically held in varying locations across Canada, USA and/or EMEA. In leadership roles, you can expect to travel once per month on average. Note: All go-to market roles will have an in-person onboarding in Toronto. What we offer We believe in working hard, and rewarding that hard work through our benefits. While not an exhaustive list, here is a glance at what we currently offer: Health and wellbeing 👶 Maternity and parental leave top-up programs 🩺 Competitive health benefits 🏝 Generous PTO policy Growth and future 📈 RSU program for most employees 💸 Retirement matching program 🔑 Free 1Password account Community 🤝 Paid volunteer days 🏆 Peer-to-peer recognition through Bonusly 🌎 Remote-first work environment *Some roles in our GTM team are currently being hired for in-person hybrid work in Toronto and Austin. These roles will specify on the posting. You belong here. 1Password is proud to be an equal opportunity employer. We are committed to fostering an inclusive, diverse and equitable workplace that is built on trust, support and respect. We welcome all individuals and do not discriminate on the basis of gender identity and expression, race, ethnicity, disability, sexual orientation, colour, religion, creed, gender, national origin, age, marital status, pregnancy, sex, citizenship, education, languages spoken or veteran status. Be yourself, find your people and share the things you love. Accommodation is available upon request at any point during our recruitment process. If you require an accommodation, please speak to your talent acquisition partner or email us at nextbit@agilebits.com and we’ll work to meet your needs. Remote work is a part of our DNA. Given that our company was founded remotely in 2005, we can safely say we're experts at building remote culture. That said, remote work at 1Password does mean working from your home country. If you've got questions or concerns about this, your talent partner would be happy to address them with you. Successful applicants will be required to complete a background check that may consist of prior employment verification, reference checks, education confirmation, criminal background, publicly available social media, credit history, or other information, as permitted by local law. 1Password uses artificial intelligence (AI) and machine learning (ML) technologies, including natural language processing and predictive analytics, to assist in the initial screening of employment applications and improve our recruitment process. See here https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf for the latest third party bias audit information. If you prefer not to have your application assessed using AI/ML features, you may opt out by completing this form https://jobs.ashbyhq.com/1password/automation-notice. For additional information see our Candidate Privacy Notice https://1password.com/files/candidate-privacy-notice.pdf.

Location: Almaty, Kazakhstan Workplace: OnSite WHY WORK AT HIGGSFIELD AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. WHAT THIS ROLE MEANS AT HIGGSFIELD Most subscription businesses lose a password. We lose GPU-seconds. When someone runs two hundred accounts off one card to harvest a per-account promotional grant, the cost lands on our compute bill the same hour, and it does not stop until somebody finds them. We have found operators doing exactly that — hundreds of accounts, synchronised signups, machine- generated emails, round-the-clock automation — and we have also found that most of our worst- margin accounts are not abusers at all, just heavy users on an unlimited plan. Telling those two apart, account by account, with evidence that survives being challenged, is this job. You are the person who finds them, proves it, and puts a number on it. You make sure: - Every enforcement action we take is backed by evidence a stranger could follow - We know what abuse cost us last month, on the same basis as last month - The detection system is measured against real cases, not against its own past decisions - When a ring changes shape, somebody notices this week — and that somebody is you WHAT YOU WILL DO Investigation & casework - Run ring investigations end to end: from a flagged account or a cost anomaly to a named cluster, its members, its signature, its lifetime economics and a recommended action. - Build the linkage yourself — shared payment instruments, IP and ASN concentration, email-stem families, registration bursts, behavioural and automation fingerprints — and know which links are evidence and which are coincidence. - Separate abuse from unprofitable-but-legitimate every single time. On an unlimited plan, negative gross margin is normal. Cost is a gate, never a trigger. - Triage the review queue the detection system produces, and feed what you learn back into it. Your adjudications are the only unbiased labels the scientist has. Evidence & defensibility - Produce evidence packages that hold up outside the company — to an external auditor, to a payment network, to a customer disputing a ban, to Legal enforcing our Terms. Our abuse work has already been used in all four contexts. - Write per-account, not per-ring, when the action is per-account. A ban list without a reason column is not evidence. - Know what our Terms of Use actually entitle us to do, and flag when the evidence supports the finding but not the action. Quantification & reporting - Own the abuse loss number: what it cost, on what basis, net of the revenue we reversed and the legitimate customers we caught by mistake. Same definition every month, written down. - Distinguish COGS burned, revenue at risk, revenue reversed and cash refunded — they are four different numbers and people will conflate them. - Build the recurring reporting that tells us whether the problem is growing, and the ad-hoc answer to "why did compute spike last Tuesday" that is due the same day. Monitoring & adaptation - Watch the detectors themselves. A rule that stops firing is a detection event, not a quiet week. - Check the instrument before explaining the movement: a missing upstream table, a silently dropped join, a vendor signal that went away. This has bitten us and it will again. - Spot new abuse patterns before they are in anybody's model — usually in a cost anomaly, a strange cohort, or a support ticket that does not fit. How we work - SQL and Python on raw payment, usage and identity data in BigQuery, without anyone preparing it for you. We use AI heavily — resourcefulness beats syntax. - Close partnership with the Antifraud data scientist (you validate what they build), Payments (chargebacks and processor signals), Support (the humans who meet your false positives) and Finance (the loss number goes in the accounts). WHO WE'RE LOOKING FOR - 2+ years doing investigative or risk analytics — fraud, abuse, trust and safety, AML, chargebacks, gaming or marketplace integrity. What matters is that you have chased real bad actors, not modelled them in the abstract. - Strong SQL, without help. Self-joins, window functions, cohort replay, and joining payments to usage to identity across messy keys. This is the single most-used skill in the role. - Python at working level for analysis — pandas, notebooks, a bit of graph work. - Investigative instinct: you follow the thread, you notice the thing that does not fit, and you can say when a pattern is a coincidence. - Evidentiary discipline: you can write up a finding so that somebody who distrusts you can check it, and you know the difference between "this looks like abuse" and "this is provable." - Unit-economics literacy: gross margin per account, what compute costs, and why a negative-margin customer may be entirely legitimate. - The judgment to escalate rather than act when the evidence is thin, and to say so in writing. - Clear written and spoken English, B2+. Backgrounds that often do well: - Fraud / risk analysts from fintech, payments, marketplaces, gaming, crypto or betting - Trust & safety investigators and platform-integrity analysts - Chargeback, dispute or AML analysts who write their own queries - Strong product or BI analysts who got handed the abuse problem and kept it WHAT THIS ROLE IS NOT This role is not a fit if you: - Want to build models full time — that is the Antifraud data scientist, and it is open - Want to do content moderation or NSFW classification - Would put an account on a ban list without being able to say why in one sentence - Treat every negative-margin account as an abuser - Need a labelled dataset or a clean table before you can start - Are uncomfortable that your work gets real people's accounts restricted, sometimes wrongly - Want predictable 9–5 workdays HIRING PROCESS - Screening call (30 min) - Hiring-manager screen (30 min) - Business case (1,5 hour) - Tech interview (1,5 hour) - Final interview (30 min) - Paid on-site trial (1 month) THE DEAL - Competitive salary in USD - Equity: participation in the company's stock option program - On-site role in Almaty, Kazakhstan - Relocation support (flight + temporary housing) - Flat structure, high autonomy, fast career growth

Location: Almaty, Kazakhstan Workplace: OnSite WHY WORK AT HIGGSFIELD AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. WHAT THIS ROLE MEANS AT HIGGSFIELD Generative video has a problem most subscription businesses don't: every unit we sell costs us real compute. A stolen password costs a streaming service nothing. An account farm on an unlimited generation plan costs us GPU-seconds, at scale, every hour it runs. We have found organised operators running hundreds of accounts on a single card, reselling unlimited generations, and harvesting per-account promotional grants at industrial scale. We have also found that most of our negative-margin accounts are not abuse at all — they are ordinary heavy users on an unlimited plan, which is a pricing problem wearing a fraud costume. Telling those two populations apart, at account level, before the money is gone, is this job. You own the question of who is taking value they did not pay for, and the system that stops them. You make sure: - We catch abuse before the compute is burned, not in a post-mortem that reconciles the loss - Every enforcement action has a measured precision, a measured cost of being wrong, and a way back for the customer we got wrong - The difference between fraud and unprofitable pricing is a number we can defend, not a vibe - When operators adapt — and they will, within days — we find out from a monitor, not from the monthly margin review WHAT YOU WILL DO Detection & scoring - Own the account-abuse scoring system end to end: signals, weights, thresholds, the scoring job, the monitoring, and the recalibration when it decays. - Build detection that fires early. A rule that catches 88% of the money on day 11 is worth far less than one that catches 60% at checkout, and you should be able to say why in dollars. - Work the two halves that actually matter together: linkage (who is connected to whom) and economics (what are they consuming). Either one alone produces a system nobody can switch on — linkage without economics flags families sharing a card, economics without linkage flags our best customers. - Treat cost as a gate, not a label. On an unlimited plan, being gross-margin negative is normal. Entity resolution & ring detection - Find rings, not just accounts: shared payment instruments, IP and ASN concentration, email-stem families, synchronised registration bursts, behavioural fingerprints, automation signatures. - Do it without a reliable device fingerprint — we do not have one today, and part of this job is telling us what it would be worth and what it would cost. - Know where graph methods break. Transitive closure through a shared card will happily merge thousands of unrelated people into one "ring"; we have done exactly that and thrown the result away. Enforcement, policy & the cost of being wrong - Design graduated, reversible actions — throttle, rate-limit, step-up verification, hold, pre-grant refusal, manual review queue, ban — and match the severity to the confidence. - Own the false-positive budget explicitly: how many paying customers are we willing to inconvenience to save a dollar of compute, and what is the appeal path for the ones we get wrong. - Build the pre-grant gates. The cheapest abuse to stop is the kind we decline to enable in the first place — a trial we do not grant costs nothing to claw back. - Partner with Payments on Stripe Radar, chargebacks and dispute economics; with Support on the queue your model creates; with Legal on what our Terms actually entitle us to do. Measurement & adversarial monitoring - Quantify what the system is worth in money — COGS avoided, net of the revenue you destroyed and the support cost you created. Keep that number current. - Run holdouts even on enforcement, wherever it is legal and safe to do so, because otherwise you will never know what your rules are worth. - Monitor for adaptation, not just drift. Model decay here is caused by an adversary, and it looks different: a signal stops firing, a ring changes shape, a cohort's behaviour shifts inside a week. - Watch your own inputs. A detection system that silently loses a feature degrades to a system that cannot reach its own threshold — and reports nothing wrong while doing it. Making it usable - Ship scores and reasons, never scores alone. An analyst, a support agent or an auditor must be able to read why an account was actioned. - Produce evidence that survives outside the company. Our abuse work has already been used in an external audit and in Terms-of-Use enforcement; write for that standard. - Work in SQL, Python and BigQuery on raw event, payment and generation data. We use AI heavily — resourcefulness beats syntax. WHO WE'RE LOOKING FOR - Experience building abuse, fraud or trust-and-safety detection that actually took action on real users — payments fraud, promo abuse, multi-accounting, bonus abuse, account takeover, marketplace or gaming abuse. Anti-money-laundering and credit-risk backgrounds transfer if the modelling was yours. - Genuine understanding of the adversarial setting: that your counterparty responds, that your training labels are generated by your own past decisions, and that offline AUC on a censored label set is close to meaningless. - Strong SQL and Python on raw event data without help: joins across payments, usage and identity, window functions, cohort replay. Gradient boosting, and the judgment to know when a two-condition rule beats a model. - Comfort with graph and linkage thinking — connected components, shared-attribute clustering, and an instinct for when a link is evidence and when it is coincidence. - Precision-first evaluation instincts: precision at the operating point, cost-weighted error, and why you would take 20% recall at 90% precision over the reverse in an enforcement system. - Unit-economics literacy: gross margin per account, what compute actually costs us, why a negative-margin customer may be entirely legitimate. - The judgment to escalate rather than act when the evidence is thin, and to say so in writing. - Clear written and spoken English, B2+. Backgrounds that often do well: - Fraud / risk data scientists from fintech, payments, marketplaces, gaming or crypto - Trust & safety and platform-integrity teams who owned detection and enforcement policy - Growth or product data scientists who ended up owning promo-abuse because nobody else would - Analysts from payment processors, PSPs or chargeback/dispute operations who moved into modelling WHAT THIS ROLE IS NOT This role is not a fit if you: - Want to build content-moderation or NSFW classification — that is a different function here - Would ship a ban list without knowing its precision - Optimize AUC on a label set your own enforcement created, and call it validated - Need a labelled fraud dataset to exist before you can start - Treat every negative-margin account as an abuser - Are uncomfortable that being right 90% of the time means being wrong about real, paying, legitimate people — and that you own what happens to them - Want predictable 9–5 workdays HIRING PROCESS - Screening call (30 min) - Hiring-manager screen (30 min) - Business case (1 hour) - Take-home with real-shaped data (7 days, ~10–12 hours of work) - Team interview (60 min) - Paid on-site trial (1 month) THE DEAL - Competitive salary in USD - Equity: participation in the company's stock option program - On-site role in Almaty, Kazakhstan - Relocation support (flight + temporary housing) - Flat structure, high autonomy, fast career growth

Location: Paris, France Workplace: Hybrid HEALTH CAN’T WAIT. Not for symptoms to get worse. Not for a six‑month appointment. Not for a system to catch up. But that’s exactly how healthcare works today. You wait, until you can’t. Alan exists to end the wait. Health is a universal right, and we believe this right can only become real when it’s coupled with prevention. We need to stop treating health as something we repair and start treating it as something we build, every day. It’s not solely a question of willpower. It’s the healthcare system itself that needs to work for everyone, in a sustainable way. So we are building the new standard in prevention insurance. Alan is the first company that integrates insurance, prevention, and care into a single, acclaimed user experience. We are on an incredible journey to build a global leading company, with a unique culture https://alan.com/en/careers. We already partner with 40K+ companies of all sizes, serving more than 1M+ members, and have reached €800M+ in ARR. Prevention as the new norm. That's what we're building with our team of 1000+ people. If it speaks to you: we're hiring across France, Spain, Belgium, and Canada. And beyond. MISSION Alan is scaling internationally (800+ employees, 100+ healthcare professionals, 5+ countries) and needs IT Engineers to build and own the internal technology platform every Alaner works on: identity and provisioning, endpoint and SaaS security, the tooling behind our clinics, and the automation that keeps IT from scaling linearly with headcount. The scope below is what the team owns, not a checklist for one person. You'll be staffed on one or two of these areas at a time, according to your strengths and interests, and it will evolve through time based on company needs and personal appetite. Staying close to users keeps us building the right things: you'll spend up to 2-3 days a month on IT support, seeing first-hand where friction lives and what's worth automating next. SCOPE ⚙️ PLATFORM & AUTOMATION - Own and extend automations on Alan Home, our internal provisioning engine - Maintain, extend and improve helpdesk automation, SaaS provisioning flows, and onboarding/offboarding pipelines - Own the meeting room AV and room-booking platform as a product, replicable across offices 🔑 IDENTITY & ACCESS - Own the IT side of the employee lifecycle (onboarding, offboarding, mobility between jobs and countries) across Google Workspace, SSO/SAML and our SaaS ecosystem. - Grow our role-based access model: extend it to more tools and refine the permission groups, so access is granted by role rather than case by case - Make employee lifecycle events reliable, fast and auditable end-to-end - Own access reviews and least-privilege models; produce and maintain the evidence our auditors rely on - Own SaaS procurement and license management: vendor relationships, renewals, and cost optimization across our stack 🔒 ENDPOINT & SAAS SECURITY - Own the Mac fleet in Kandji: enrollment at scale, role-based blueprints, fleet compliance - Cloudflare WARP, SaaS security controls - Maintain and strengthen our ISO 27001 certification and drive ACPR and pentest remediation on the endpoint and platform scope 🩺 HEALTH PROFESSIONALS IT - The IT layer behind Alan's clinics: practitioner tooling, equipment, access - Role and permission automation for healthcare professionals, and their support and escalation process 🌍 INTERNATIONALISATION - Make international expansion something IT accelerates, not something it slows down: a repeatable process where every new market (Canada, KSA, Armenia...) launches on our standard stack from day one - Bring acquired entities onto that same platform MILESTONES First 3 months - Acquire technical knowledge on Alan's platform: Alan Home, Google Workspace/SSO, Kandji, Cloudflare WARP - Take one project end-to-end and ship a first increment - Join the IT oncall team as technical escalation First 6 months - Own a workstream end-to-end - Deliver one automation or hardening initiative end-to-end - Take up documentation and automation on your scope and reduce significantly the bus factor on it - Mentor IT teammates on your core expertise First year - Deliver measurable IT toil reduction on your scope - Set the technical standards on your domain: how we build, document and review it - Build strong cross-functional partnerships (Engineering, Security, Workplace, Clinic, People, Audit) - Contribute to hiring and onboarding new teammates 3 years - Lead major projects end-to-end across several communities - Be the reference the team relies on across at least two domains - Mentor the IT team and beyond, and scale IT without a linear increase in manual work As the community grows, there is room to take on more responsibility: leading a crew, owning cross-community projects, mentoring, hiring. WHAT WE'RE LOOKING FOR Must-have - Technical/hard skills: - 5+ years in IT engineering, platform, systems or corporate engineering, with real ownership of production-facing systems - Depth in at least one area (platform & automation, identity, endpoint & security) and demonstrated range beyond it. - You write code: not necessarily as a full-time software engineer, but Python, APIs and pull requests in a shared repo should feel normal - Structured problem-solving: diagnoses methodically, asks the right clarifying questions, thinks about failure modes and rollback - Comfort with regulated environments: health data, ACPR, ISO 27001, HDS - Automation & AI appetite: uses AI tools smartly to accelerate their own delivery, with an instinct for what should be automated or delegated to AI rather than repeated Must-have - Behavioral / soft skills: - Ownership & autonomy: drives topics forward without hand-holding, including when they cross into someone else's perimeter - Written communication: Alan is written-first; decisions get argued in public documents and challenged by people outside your team - Pragmatic judgment: balances "perfect" vs. "good enough", decides with incomplete information - Documentation culture: reduces bus factor through clear documentation and knowledge sharing Nice-to-have skills / Bonus points if you have: - Experience with an internal provisioning or IdP-driven automation platform - Kandji or another MDM at scale - Cloudflare Zero Trust / WARP, Datadog - Audit remediation experience (ISO 27001, HDS) - Multi-country rollouts, or IT integration after an acquisition - Having mentored, coached or led a (small) crew - Health or healthtech ecosystem familiarity Languages: Fluent English & Professional French

Location: Amsterdam, Netherlands; Berlin, Germany; London, United Kingdom; Poland; Prague, Czech Republic; Tel Aviv, Israel; Zurich, Switzerland About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on. Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production. Your responsibilities Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff. Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components. Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost. Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices. Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets. Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact. Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs. Must-haves A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline. A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes. Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs. Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice-to-haves First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals. Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems. Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: United States About Toloka At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing ove r 100 countries and speaking 40+ languages. We are a well-funded startup with an enviable portfolio of clients including Anthropic, Amazon, Microsoft, Poolside, Recraft, and Shopify. Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin, CTO of Shopify and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world : USA, UK, the Netherlands, Serbia , and more. Role Description We are seeking an exceptional Program Director to own and scale the execution of Enterprise fine-tuning projects across a major client portfolio. This role focuses on operational excellence and flawless delivery, working in close partnership with business development, product, and engineering teams to drive revenue growth through exceptional client outcomes. As Program Director, you will own the process management and client engagement behind these projects. You will work directly with enterprise engineering, platform, and product teams to turn a business problem into a scoped, delivered fine-tuning engagement. This is a senior, hands-on role: you will run the work yourself, not just oversee it. You will combine consulting-grade program management with a working understanding of how fine-tuning projects run, and experience navigating enterprise procurement and IT. What you’ll do Be the senior enterprise engagement lead. Run discovery with the client: stakeholder interviews, use-case prioritisation, business case and ROI, then scope and deliver the engagement end to end, including model hosting, SLAs and security reviews. Improve GenAI systems already in production, particularly across quality, cost, or latency. Take ownership of active client projects, managing scope, timelines, and stakeholders. Navigate enterprise procurement, IT infrastructure, and security processes on the client side. Our clients are tech-forward enterprises. Your counterparts are CTOs and platform, infrastructure and ML engineering leads, not procurement desks alone. Translate between client product and engineering buyers and our internal data and machine learning teams. Partner with the sales team on opportunities and help shape offerings as the business grows. Build repeatable processes and playbooks so the practice can scale across new clients and industries. Required Skills and Experience Strong consulting experience with a record of hands-on client delivery. Working technical fluency in LLMs and fine-tuning. You will partner closely with our ML engineers; you don't need to be one, and this is not a coding role. Product and process management skills, with the ability to structure ambiguous problems and drive them to completion. Experience working with large enterprises, including their procurement processes and IT infrastructure. Excellent communication skills with technical and non-technical stakeholders, including senior client leadership. STEM background preferred. Why This Role Fine-tuning needs three things: compute, which is commoditised; ML engineers, of whom there are more every year; and high-quality data, which is what actually limits model quality. Toloka produces that data, which puts us in a position which pure fine-tuning shops are not. You would join on the ground floor of this practice and help build it, including the forward-deployed team as it grows. What we can offer You will be part of an international, dynamic environment that drives innovation and sets new standards in the AI and technology sector. Competitive compensation package including base salary, bonus, and ESOP. Paid PTO and benefits will vary depending on location. We offer a full remote or hybrid model (if you are based in NL or Serbia). IT setup and home office allowances. Equal Opportunity Employer: Toloka is committed to providing equal opportunity and fostering an inclusive environment. We welcome applications from all qualified individuals and do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, gender identity, age, marital status, veteran status, disability, or any other characteristic protected by applicable law. Selection decisions are made based on qualifications, merit, and business need. [Important Notice] Scam Alert Regarding Fake Job Postings It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants. Please be aware: Official Communication: Our recruiting team will only contact you from an official " toloka.ai " email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc, or other personal or seemingly business email accounts. Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process. Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn. We are taking this matter very seriously and are working with the appropriate parties to resolve it. Thank you for your vigilance! To learn how we collect, use, disclose, and store personal data, check out our Privacy Notice .

Location: European Union About Toloka At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing ove r 100 countries and speaking 40+ languages. We are a well-funded startup with an enviable portfolio of clients including Anthropic, Amazon, Microsoft, Poolside, Recraft, and Shopify. Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin, CTO of Shopify and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world : USA, UK, the Netherlands, Serbia , and more. Role Description We are seeking an exceptional Program Director to own and scale the execution of Enterprise fine-tuning projects across a major client portfolio. This role focuses on operational excellence and flawless delivery, working in close partnership with business development, product, and engineering teams to drive revenue growth through exceptional client outcomes. As Program Director, you will own the process management and client engagement behind these projects. You will work directly with enterprise engineering, platform, and product teams to turn a business problem into a scoped, delivered fine-tuning engagement. This is a senior, hands-on role: you will run the work yourself, not just oversee it. You will combine consulting-grade program management with a working understanding of how fine-tuning projects run, and experience navigating enterprise procurement and IT. What you’ll do Be the senior enterprise engagement lead. Run discovery with the client: stakeholder interviews, use-case prioritisation, business case and ROI, then scope and deliver the engagement end to end, including model hosting, SLAs and security reviews. Improve GenAI systems already in production, particularly across quality, cost, or latency. Take ownership of active client projects, managing scope, timelines, and stakeholders. Navigate enterprise procurement, IT infrastructure, and security processes on the client side. Our clients are tech-forward enterprises. Your counterparts are CTOs and platform, infrastructure and ML engineering leads, not procurement desks alone. Translate between client product and engineering buyers and our internal data and machine learning teams. Partner with the sales team on opportunities and help shape offerings as the business grows. Build repeatable processes and playbooks so the practice can scale across new clients and industries. Required Skills and Experience Strong consulting experience with a record of hands-on client delivery. Working technical fluency in LLMs and fine-tuning. You will partner closely with our ML engineers; you don't need to be one, and this is not a coding role. Product and process management skills, with the ability to structure ambiguous problems and drive them to completion. Experience working with large enterprises, including their procurement processes and IT infrastructure. Excellent communication skills with technical and non-technical stakeholders, including senior client leadership. STEM background preferred. Why This Role Fine-tuning needs three things: compute, which is commoditised; ML engineers, of whom there are more every year; and high-quality data, which is what actually limits model quality. Toloka produces that data, which puts us in a position which pure fine-tuning shops are not. You would join on the ground floor of this practice and help build it, including the forward-deployed team as it grows. What we can offer You will be part of an international, dynamic environment that drives innovation and sets new standards in the AI and technology sector. Competitive compensation package including base salary, bonus, and ESOP. Paid PTO and benefits will vary depending on location. We offer a full remote or hybrid model (if you are based in NL or Serbia). IT setup and home office allowances. Equal Opportunity Employer: Toloka is committed to providing equal opportunity and fostering an inclusive environment. We welcome applications from all qualified individuals and do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, gender identity, age, marital status, veteran status, disability, or any other characteristic protected by applicable law. Selection decisions are made based on qualifications, merit, and business need. [Important Notice] Scam Alert Regarding Fake Job Postings It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants. Please be aware: Official Communication: Our recruiting team will only contact you from an official " toloka.ai " email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc, or other personal or seemingly business email accounts. Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process. Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn. We are taking this matter very seriously and are working with the appropriate parties to resolve it. Thank you for your vigilance! To learn how we collect, use, disclose, and store personal data, check out our Privacy Notice .

Location: Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. About the Role We are at an inflection point where AI is fundamentally reshaping what products can do and how users experience them. We're not just looking for a product manager — we're looking for a hybrid product builder who truly understands AI capabilities and can translate technical potential into real user value. You will lead end-to-end product design for LLM / Agent-powered applications — from zero to one — across domains including intelligent customer service, personalized recommendations, AI assistants, and automated workflows. You are the critical connector between user insights, AI technical capabilities, and business objectives: someone who can discuss RAG retrieval strategies and multi-agent orchestration with ML engineers, while clearly articulating product value and delivery roadmaps to business stakeholders. If you have genuine passion for AI-native products and the ability to define clear product direction amid ambiguity and rapid change, we'd love to build the next generation of AI applications together. Key Responsibilities End-to-End AI Product Lifecycle Management Own the full product lifecycle of AI applications — including intelligent chatbots, AI assistants, recommendation systems, and automated workflows — from requirements definition and product design through to launch and delivery. Produce high-quality PRDs, interaction flow diagrams, and acceptance criteria while driving cross-functional teams to execute efficiently. LLM / Agent Capability Productization Deeply engage in Agent product design, including task planning workflows, tool-calling strategies (Function Calling / MCP), context management mechanisms, multi-agent orchestration logic, and graceful failure/fallback handling. Translate underlying model capabilities into meaningful, perceivable user value. AI Evaluation Framework & Quality Standards Build Harness evaluation frameworks for AI products — designing test scenario sets, evaluation metric systems (accuracy, hallucination rate, task completion rate, etc.), and regression test case libraries. Independently assess AI capability boundaries and drive continuous model iteration and product quality improvement. Conversational Product Design & Knowledge Engineering Lead platform architecture planning for intelligent customer service and conversational assistant products, covering knowledge base structure design, dialogue flow and SOP design, corpus annotation and training strategy, intelligent reply generation, and case summarization. Leverage large-scale data analysis to continuously optimize conversation quality and issue resolution rates. Personalization Engines & Generative UI Products Collaborate deeply with ML and data teams to design recommendation strategies that deliver truly personalized, individualized user experiences. Define generative UI product requirements and drive growth in core business metrics including CTR, conversion rate, and user retention. Establish comprehensive attribution analysis frameworks for recommendation effectiveness. AI Capability Integration with Business Scenarios Develop a thorough understanding of business goals and user pain points. Proactively identify opportunities to apply AI technologies — including RAG, Prompt Engineering, and multimodal capabilities — to concrete use cases. Define clear product evolution roadmaps that balance technical feasibility, user experience, and commercial value. Cross-Functional Collaboration & AI-Native Product Culture Act as the product Owner in close collaboration with algorithm, engineering, data, design, operations, and business teams. Maintain a strong sense of ownership in a fast-moving AI-native environment, continuously track industry developments, and rapidly translate emerging AI capabilities into product innovation opportunities. Requirements Product Experience : 3+ years of product management experience, with at least 1 year of direct hands-on experience delivering AI application products, AIGC products, or Agent products. Must have fully shipped at least one AI-related feature module or standalone product. AI Technical Understanding : Deep understanding of the productization of mainstream AI technologies, including but not limited to: LLM Prompt Engineering, RAG (Retrieval-Augmented Generation) architecture, Agent fundamentals (tool calling / task planning / context window management), and conversational system design. Ability to independently evaluate the product feasibility of technical proposals. Evaluation & Data Capabilities : Proven ability to design AI product evaluation frameworks — independently defining evaluation metrics, building test case sets, and tracking product performance through data analysis. Familiarity with A/B experiment design and a strong data-driven decision-making mindset. Documentation & Communication Skills : Ability to write structured, logically rigorous PRDs, technical requirement documents, and flow diagrams. Excellent cross-functional communication skills with the ability to accurately bridge information between technical and business teams, eliminating information gaps. User Insight & Product Thinking : Sharp ability to translate ambiguous user needs into clearly defined product requirements. Skilled at finding the right product balance between AI capability boundaries and user expectations — avoiding both overpromising and underutilizing model capabilities. Learning Agility & Ownership Mindset : Sustained enthusiasm and capacity for continuous learning in a rapidly evolving AI landscape. Strong sense of ownership — able to proactively define problems, drive decisions, and take accountability for outcomes in highly ambiguous environments. Nice to Have Familiarity with cutting-edge AI engineering practices including MCP ( Model Context Protocol ), Function Calling, and multi-agent orchestration frameworks (e.g., LangChain / AutoGen / CrewAI), enabling deep technical dialogue with engineering teams. Experience with AI Harness / Eval / Benchmark platform product design or usage, with involvement in establishing and maintaining LLM evaluation systems. Background in Fintech / e-commerce / SaaS industries, with an understanding of the unique product design requirements for AI in high-concurrency, compliance-sensitive environments. Bilingual fluency in Chinese and English (spoken and written), with the ability to independently drive product collaboration and cross-cultural communication within international teams. Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

Location: Bengaluru, India We are looking for a Senior AI Quality Engineer (L3+) with strong Python skills and hands-on experience testing AI and ML systems. You will analyze requirements, define evaluation strategies, build automated checks, validate models and outputs, test APIs and data pipelines, verify defects through resolution, and contribute to release readiness for your assigned product area. You will both evaluate AI systems and design, build, and operate QE agents for the software testing life cycle. AI-assisted work is part of everyday QE practice on this engagement, with Ragas, DeepEval, promptfoo, Cursor, and other AI and ML tools used for evaluation, scripting, test generation, analysis, and maintenance. You will also build golden datasets, calibrate LLM-as-judge methods, test agentic workflows and RAG systems, implement self-healing and intelligent test approaches, and diagnose quality, safety, performance, and cost failures across distributed AI services. This position is intended for Hyderabad-based candidates who are available to work from the office. The client delivers AI agents, retrieval systems, models, and data pipelines across a broad technology landscape. Quality is part of delivery through evaluation gates, automated regression, model and data validation, security and privacy checks, and evidence that a release is ready. Python is the primary language for AI evaluation, model validation, API testing, data-pipeline quality, and QE agent design. The role combines deterministic automation with probabilistic evaluation to assess AI behavior across models, data, retrieval, tools, and integration surfaces, and designs and operates agents that support the software testing life cycle. Analyze requirements and define evaluation strategies, golden datasets, regression benchmarks, baselines, thresholds, and blocking metrics with domain-expert review. Design, build, and orchestrate AI agents, persona-based workflows, and reusable skills for the STLC using LangChain, LangGraph, or Semantic Kernel. Build automated evaluations and benchmarks for LLMs, agents, RAG, retrieval, tool trajectories, and contracts using Ragas, DeepEval, and promptfoo. Calibrate LLM-as-judge against human grading, manage non-determinism through repeated runs, and detect regression and drift. Write and maintain Python and pytest automation for AI, ML, API, data, and integration workflows. Use Cursor and agentic tools to analyze requirements, generate and review tests, and maintain evaluation suites. Validate deep-learning, reinforcement-learning, and predictive models using LangChain. Build AI-assisted STLC workflows for requirements analysis, test design, script generation, execution, self-healing, failure analysis, and defect triage, plus intelligent test selection and defect prediction. Integrate LLMs, APIs, embeddings, vector databases, retrieval pipelines, and enterprise data sources into QE frameworks using Python. Test REST and streaming APIs, agent tools, and RAG and MCP integrations, including authentication, errors, retries, and recovery. Test data and retrieval pipelines for schema integrity, lineage, idempotency, fallback, promotion gates, and rollback. Integrate evaluations, benchmarks, and agent workflows into QE frameworks and CI/CD on GitHub Actions, review Allure results, and keep TestRail aligned with automated coverage. Test prompt injection, jailbreaks, unsafe tool use, data exfiltration, access control, PII controls, and guardrails. Measure accuracy, relevance, groundedness, hallucination, retrieval quality, agent reliability, latency, throughput, token use, and cost, and diagnose distributed failures. Implement tracing, monitoring, and production evaluation using Langfuse, LangSmith, or a comparable AI observability platform. Deploy and operate QE agents on Amazon Bedrock AgentCore or a comparable agent platform, with governance and human oversight. Deploy and validate AI and ML solutions on AWS or Azure, including secrets, database services, and cloud-native test infrastructure. Report, track, and verify defects in Jira, and work with domain experts, product, and engineering on traceable coverage and untested scope. Contribute to release readiness for the assigned product area without owning sign-off for the whole team. Strong Python proficiency with pytest for test and evaluation automation. Hands-on experience building and orchestrating AI agents and agentic workflows with LangChain, LangGraph, Semantic Kernel, or comparable frameworks. Hands-on experience building AI evaluations and benchmarks with Ragas, DeepEval, promptfoo, or equivalent tools. Hands-on use of Cursor or agentic development tools for test generation and maintenance. Experience defining AI evaluation strategies, golden datasets, regression benchmarks, and LLM-as-judge calibration, including non-determinism and drift. Experience validating deep-learning, reinforcement-learning, and predictive models with LangChain. Experience building AI-assisted STLC workflows for requirements analysis, test design, script generation, execution, self-healing, failure analysis, defect triage, intelligent test selection, and defect prediction. Experience integrating LLMs, APIs, embeddings, vector databases, and retrieval pipelines with automation frameworks in Python. Experience testing REST and streaming APIs, agent tools, RAG workflows, and MCP integrations. Experience testing data and retrieval pipelines for correctness, lineage, and safe promotion. Experience integrating AI evaluation and agent workflows with automation frameworks and CI/CD using GitHub Actions, Allure, TestRail, or equivalent tools. Experience testing AI security, privacy, access control, and guardrails. Experience measuring accuracy, relevance, groundedness, hallucination, retrieval quality, agent reliability, latency, throughput, token use, and cost, and diagnosing distributed failures. Experience with AI tracing, monitoring, and production evaluation using Langfuse, LangSmith, or comparable tools. Familiarity with AWS, Azure, or GCP cloud AI services and agent platforms for deploying and validating AI and ML solutions. Experience deploying and operating agents on Amazon Bedrock AgentCore or a comparable agent platform, with governance and human oversight. Experience managing defects through resolution in Jira or an equivalent tool. Ability to work with domain experts, product, and engineering on ground truth and coverage gaps. Experience contributing to release readiness for an assigned product area. Playwright and TypeScript experience for UI and API automation. Real-device and cross-browser execution using LambdaTest, Sauce Labs, or an equivalent platform. Knowledge of AI-driven test optimization and coverage analytics using SeaLights or an equivalent platform. Experience contributing reusable components to shared automation frameworks and reviewing automation code through Git and GitHub workflows. Experience managing test data and troubleshooting test environments needed for reliable execution. Experience triaging security findings and validating operational readiness, monitoring, rollback, and recovery controls. Experience producing audit-ready evaluation reports and improving shared evaluation patterns, automation libraries, and datasets.

Location: Mexico Paired is a global staffing and recruiting agency that specializes in pairing remote work with top-tier talent. We admire the importance of innovative social media strategies and are committed to connecting talented individuals with great companies that need their unique skills. Our mission is to provide great jobs to talented people, no matter where they are located. We're seeking a Creative Strategist to drive our client's paid advertising performance through high-converting ad concepts and data-driven iterations. You'll generate fresh creative angles, script compelling ads, and work closely with our designer/video editor and media buyer in a fast-paced feedback loop. This role requires deep understanding of DTC ecommerce, consumer psychology, and what makes ads stop the scroll and drive purchases. Responsibilities Generate multiple creative angles and concepts weekly based on performance data, customer insights, and market trends Write scripts for various ad formats including UGC, VSLs, static ads, and short-form video content Review campaign performance feedback from the media buyer and use data to inform next creative iterations Provide clear direction and feedback to the design/video team to ensure effective execution Monitor competitor ads, viral trends, and platform best practices across Meta and Instagram Work in weekly cycles with the media buyer and creative team to test, learn, and scale winning concepts Requirements Proven track record developing creative for DTC ecommerce brands in performance marketing environments Strong ability to craft hooks, angles, and messaging that convert, backed by understanding of consumer psychology Comfortable interpreting ad performance metrics and feedback to guide creative decisions Experience conceptualizing and scripting multiple ad formats (UGC, VSLs, static, video ads) We require a portfolio Ability to produce high-quality concepts quickly and iterate based on data Clear, proactive communicator who thrives in collaborative feedback loops Benefits USD Salary. Ability to work remotely.

Location: United States Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE The Senior Principal Software Engineer is responsible for shaping and evolving the company’s technical landscape. In addition to designing, developing, and maintaining core systems, the Senior Principal Software Engineer provides strategic guidance to align technology initiatives with business goals. This role is vital in ensuring that the platform is secure, scalable, and performant—capable of supporting rapid growth and driving innovation. _______________________________________________________________________ RESPONSIBILITIES TECHNICAL STRATEGY & ARCHITECTURE - Define and drive the overarching technical vision, ensuring the platform meets current and future scalability, performance, and security needs - Evaluate and select tools, frameworks, and architectures to maintain a state-of-the-art technology stack LEADERSHIP & MENTORSHIP - Provide technical leadership and guidance to the engineering organization, setting best practices and standards. - Coach and mentor engineers, fostering a culture of continuous learning and collaboration Innovation & Research - Investigate emerging technologies, frameworks, and best practices - Lead prototyping initiatives and proof-of-concepts that can transform the platform’s capabilities SCALABILITY & PERFORMANCE - Ensure the platform is designed for high performance and can seamlessly handle increasing user loads - Oversee performance optimization, load balancing, and capacity planning strategies RELIABILITY & AVAILABILITY - Design fault-tolerant, highly available systems that minimize downtime and deliver a seamless user experience Infrastructure Automation - Advocate for and implement Infrastructure as Code (IaC) principles, CI/CD pipelines, and automation best practices - Continuously refine deployment, testing, and operations processes to improve efficiency SECURITY & COMPLIANCE - Collaborate with security experts to ensure platform integrity, compliance with industry standards, and protection of sensitive data - Proactively address security vulnerabilities and champion secure coding practices CROSS-FUNCTIONAL COLLABORATION - Work closely with product managers, designers, and other stakeholders to ensure technical initiatives support business objectives - Drive alignment between engineering roadmaps and product strategies TECHNICAL PROBLEM-SOLVING - Tackle complex architectural and technical issues, providing clear direction and innovative solutions - Serve as an escalation point for critical system challenges CODE QUALITY & REVIEWS - Uphold coding standards through thorough code reviews, ensuring high-quality, maintainable codebases - Establish and enforce best practices around testing, documentation, and version control DOCUMENTATION & KNOWLEDGE SHARING - Produce comprehensive technical documentation, including architectural diagrams, design guidelines, and operational runbooks - Promote a transparent engineering culture by sharing insights and successes across the organization - Take part in on-call rotation for your team, respond to incidents, debug production issues, and drive continuous improvement of system reliability _______________________________________________________________________ QUALIFICATIONS ● 12+ years of software engineering experience with demonstrated expertise across multiple domains (SDLC, AI engineering, corporate systems, etc) ● Extensive software engineering experience, with a track record in designing and implementing large-scale, distributed systems ● Deep technical expertise: Proficiency in multiple programming languages, cloud platforms (e.g., AWS, Azure, GCP), and modern development frameworks ● Leadership acumen: Demonstrated ability to lead diverse engineering teams, inspire innovation, and drive successful outcomes ● Architectural vision: Proven skill in defining and driving architectural roadmaps that align with evolving business needs. ● Problem-solving ability: Expertise in diagnosing complex system issues and designing robust, scalable solutions ● Communication skills: Excellent written and verbal communication skills, capable of influencing both technical and non-technical stakeholders. ● Security conscious: Solid understanding of security best practices, compliance standards, and data protection ● Continuous improvement mindset: Passion for optimizing processes, toolchains, and workflows ● Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience As a Senior Principal Software Engineer, you will not only architect innovative solutions but also shape the technical culture. Your leadership and expertise will be pivotal in building a resilient, cutting-edge platform that supports rapid growth and drives long-term success. Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $219K – $352K base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: New York, United States Who We Are At OKX, we believe the future will be reshaped by crypto and blockchain technology. We operate a leading global crypto platform and build products and services designed to expand access to the digital-asset ecosystem. Across our global organization, we value ownership, sound judgment, collaboration, innovation, and the ability to operate effectively in a fast-moving and continuously evolving environment. Recruiting should insert the current approved OKX corporate “Who We Are” language when the position is posted. About the Team The Fraud Investigations Team (FIT) is a First Line of Defense function within OKX’s Risk organization responsible for identifying, assessing, investigating, and helping manage significant internal and external fraud risks affecting the company, its customers, personnel, and operations. FIT conducts and supports complex investigations involving digital assets, internal and external fraud, employee misconduct, insider threats, unauthorized access or misuse of information, vendor and third-party misconduct, account compromise, social engineering, collusion, conflicts of interest, and other significant fraud-related matters. The team works closely with Legal, HR, Information Security,Engineering, Physical Security, Compliance, Finance, Operations, and other functions across OKX. About the Opportunity We are looking for an experienced Senior Analyst, Blockchain Investigations & Fraud Intelligence to join FIT. This is first and foremost a blockchain investigations role requiring significant hands-on expertise tracing digital assets across complex blockchain ecosystems. The successful candidate must be capable of independently conducting sophisticated on-chain investigations, developing and testing attribution hypotheses, identifying relationships among wallets and entities, following assets through multiple chains and protocols, and translating highly technical blockchain activity into clear investigative findings. Blockchain analysis is a specialized investigative discipline. Accordingly, we are seeking someone who understands not only how to operate commercial tracing platforms, but also the underlying blockchain architecture, transactional mechanics, attribution methodologies, clustering techniques, tracing limitations, and evidentiary considerations necessary to reach reliable conclusions. The role extends beyond on-chain analysis. The Senior Analyst will combine blockchain intelligence with enterprise data, system logs, transactional records, open-source information, and other evidence to support complex fraud and insider-risk investigations. The position will also provide analytical support to the Global Physical Security Team (PST) on selected protective-intelligence and threat-assessment matters. The Senior Analyst will directly manage one Analyst and will be expected to serve as a subject-matter resource for blockchain investigations and analytical methodology across FIT. What You’ll Be Doing Blockchain Investigations & Digital-Asset Intelligence Lead and conduct complex blockchain investigations and transaction tracing across multiple wallets, counterparties, entities, blockchains, tokens, protocols, and digital-asset ecosystems. Trace the origin, movement, conversion, layering, consolidation, and ultimate disposition of digital assets , including activity spanning multiple intermediaries and blockchain environments. Conduct investigations using tools such as Chainalysis Reactor , TRM Labs, Elliptic, or comparable blockchain intelligence platforms , while understanding the methodologies and limitations underlying platform-generated attribution. Analyze activity involving centralized exchanges, self-hosted wallets, decentralized exchanges, cross-chain bridges, mixers, privacy-enhancing technologies, DeFi protocols, smart contracts, stablecoins, NFTs, OTC activity, gambling platforms, and other relevant ecosystems . Trace assets across multiple chains and cross-chain transactions , identifying continuity of funds where technically supportable and clearly documenting assumptions or limitations where definitive attribution is not possible. Analyze transaction graphs, address relationships, behavioral patterns, clusters, counterparties, timing, amounts, transaction sequencing, and other relevant blockchain indicators. Understand and appropriately apply wallet-clustering and attribution methodologies , including the limitations and potential for false attribution associated with particular heuristics. Independently evaluate blockchain intelligence rather than relying solely on automated labels, risk scores, or vendor-generated attribution. Corroborate on-chain findings, where appropriate, with internal account records, KYC / KYB information, transaction data, access information, open-source intelligence, legal-process returns, or other available evidence . Identify relationships among blockchain addresses, OKX accounts, external counterparties, individuals, organizations, vendors, affiliates, and other relevant entities. Reconstruct complex transaction flows and create clear fund-flow diagrams, transaction maps, timelines, and visualizations that allow investigators and nontechnical stakeholders to understand the movement of assets. Analyze blockchain activity associated with suspected fraud , theft, account takeover, social engineering, insider activity, collusion, payment diversion, asset misappropriation, or other misconduct . Identify new wallets, counterparties, entities, or transactional patterns that may generate additional investigative leads. Clearly document the methodology, assumptions, confidence level, and limitations associated with blockchain findings. Distinguish between confirmed attribution , vendor attribution, analytical inference, behavioral similarity, and an unverified investigative hypothesis . Avoid presenting blockchain proximity, exposure, clustering, or a commercial risk score alone as proof of ownership, control, intent, or misconduct. Maintain current knowledge of emerging blockchain technologies, protocols, tracing methodologies, obfuscation techniques, fraud typologies, and developments affecting blockchain attribution or investigations . Fraud Investigations & Investigative Intelligence Conduct and support investigations involving internal and external fraud , employee misconduct, insider threats, vendor and third-party misconduct, collusion, conflicts of interest, asset misappropriation, unauthorized access, credential misuse, and other significant fraud risks . Combine blockchain findings with off-chain evidence to develop a comprehensive investigative picture rather than treating blockchain activity in isolation . Develop investigative hypotheses and objectively test those hypotheses against available evidence, including information that supports, contradicts, or fails to establish the hypothesis. Conduct timeline reconstruction, link analysis, relationship mapping, pattern analysis, clustering, and comparative analysis across individuals, accounts, wallets, devices, systems, transactions, and entities. Support investigations involving account takeover, impersonation, social engineering, business-email compromise, payment diversion, affiliate misconduct, and trusted-party abuse , particularly where a digital-asset, employee, vendor, or enterprise nexus exists. Analyze vendor, affiliate, partner, and other third-party activity for indicators of billing irregularities, undisclosed relationships, conflicts of interest, unusual payments, control circumvention, or other potential misconduct. Support investigative interviews by developing transaction timelines, identifying inconsistencies or information gaps, organizing evidence, and identifying appropriate areas for follow-up. Enterprise Data & Insider-Risk Analytics Analyze appropriately authorized information including system and access logs, authentication records, audit trails, customer-account activity, KYC / KYB information, transaction records, payment information, case-management records, vendor information, and relevant security telemetry . Correlate blockchain activity with enterprise data to identify possible connections among wallets, accounts, employees, customers, vendors, devices, transactions, and other relevant entities . Support investigations involving suspected unauthorized access, information misuse or exfiltration, credential compromise, control circumvention, unauthorized disclosure, or abuse of privileged access. Identify anomalous behavior or access patterns that may warrant additional investigation. Develop repeatable analytical methodologies capable of processing and correlating information from disparate systems. Use appropriate scripting, database querying, data visualization, and analytical technologies to efficiently analyze large or complex datasets. Investigative Reporting & Evidence Prepare clear, concise, and well-supported blockchain investigation reports, investigative memoranda, executive summaries, transaction-flow diagrams, link charts, timelines, and other analytical products . Explain complex blockchain concepts and transaction activity in plain language suitable for investigators, senior management, Legal, regulators, or law enforcement , as appropriate. Clearly distinguish among allegations, investigative leads, known facts, third-party attribution , analytical judgments, assumptions, information gaps, and substantiated conclusions . Ensure analytical conclusions are proportionate to the evidence and do not imply greater certainty than the underlying blockchain or other data supports. Maintain sufficient documentation to allow significant blockchain findings to be reviewed, reproduced, and understood by another qualified analyst . Preserve and handle investigative records in accordance with applicable evidence-preservation, chain-of-custody, confidentiality, privacy, access-control, and need-to-know requirements . Support appropriately authorized law-enforcement, regulatory, litigation, or legal matters in coordination with the appropriate company functions. Protective Intelligence & Physical Security Support Provide analytical support to PST on selected matters involving threats or concerning activity directed toward employees, executives, offices, events, or other company interests. Conduct authorized open-source, link, timeline, blockchain, financial, or other analytical research where relevant to understanding the identity, relationships, capabilities, or activity associated with a potential threat. Assist in evaluating available information relating to credibility, corroboration, intent, capability, access or opportunity, targeting, escalation, timing, and other relevant indicators . Prepare objective analytical products identifying known facts, analytical judgments, material information gaps, uncertainties, and appropriate confidence levels. Support PST’s assessment while preserving PST’s responsibility for protective-security decisions and operational response . Leadership & Development Directly manage and develop one Junior Analyst, including work allocation, coaching, technical development, quality assurance, and review of analytical work product . Serve as a FIT subject-matter resource for blockchain investigations and on-chain analytical methodology . Review blockchain analysis for technical accuracy, appropriate methodology, corroboration, reasonable attribution, and evidentiary support. Train and mentor junior personnel in transaction tracing, blockchain intelligence platforms, analytical reasoning, documentation, and investigative methodology. Help establish consistent standards for blockchain investigations, attribution , documentation, quality assurance, and reporting . Participate in time-sensitive investigations affecting a global organization, including occasional work outside normal business hours when required. What We Look For In You 7+ years of relevant investigative or analytical experience , with meaningful professional experience specifically conducting cryptocurrency or blockchain investigations . Demonstrated hands-on expertise independently conducting complex blockchain tracing investigations , rather than solely reviewing blockchain alerts or commercial risk scores. Advanced proficiency with one or more blockchain intelligence platforms such as Chainalysis Reactor , TRM Labs, Elliptic, or comparable technology . Strong understanding of how blockchain intelligence platforms derive attribution, clustering, exposure, and risk information—and the limitations associated with those methodologies . Demonstrated understanding of blockchain fundamentals, including wallets and addresses, transactions, UTXO and account-based models, tokens, smart contracts, block explorers, transaction fees, confirmations, and blockchain-specific transactional structures . Strong understanding of digital-asset ecosystems including centralized exchanges, self-hosted wallets, DeFi , DEXs, stablecoins, cross-chain bridges, mixers, privacy-enhancing mechanisms, and other relevant technologies . Demonstrated ability to trace assets across multiple chains, protocols, and intermediaries and recognize when technical limitations prevent definitive continuity or attribution. Experience conducting transaction-graph analysis, wallet attribution , clustering, counterparty analysis, transaction-flow reconstruction, and investigative link analysis . Ability to critically assess blockchain attribution and distinguish among technical facts, commercial vendor intelligence, analytical inference, and unsupported assumptions . Experience integrating blockchain intelligence with off-chain evidence and enterprise information to develop investigative conclusions. Strong knowledge of fraud-investigation principles including corroboration, source evaluation, evidence preservation, timeline development, hypothesis testing, and documentation. Experience analyzing large or complex datasets and familiarity with tools such as SQL , advanced Excel, Python, Splunk, or comparable data-analysis technologies . Ability to clearly explain technically complex blockchain findings to audiences that may have little or no blockchain expertise. Strong investigative writing skills and demonstrated ability to produce accurate, concise, and defensible analytical products. Sound judgment and ability to work effectively where evidence is incomplete, conflicting, or evolving. Demonstrated discretion when handling sensitive employee, customer, investigative, security, or company information. Demonstrated experience mentoring, supervising, or reviewing the work of junior analysts or investigators. Nice to Haves Experience conducting blockchain investigations within a cryptocurrency exchange, blockchain analytics company, law-enforcement agency, regulatory organization, financial institution, intelligence function, or investigative consulting environment . Experience investigating digital-asset matters involving fraud proceeds, theft, account compromise, insider activity, social engineering, asset tracing, or complex cross-chain movement . Experience supporting asset recovery, law-enforcement referrals, subpoenas/legal process, civil litigation, regulatory inquiries, or other matters requiring defensible blockchain analysis . Experience investigating insider threats, employee misconduct, unauthorized access, data exfiltration, credential compromise, vendor fraud, conflicts of interest, or trusted-party abuse. Experience with OSINT, digital forensics, enterprise logs, security telemetry, or identity and access-management information . Experience creating custom blockchain analytics through APIs, SQL , Python, blockchain explorers, node data, or other raw-data sources , rather than relying exclusively on commercial graphical interfaces. Relevant blockchain-specific training or certifications, including certifications associated with Chainalysis , TRM Labs, or comparable blockchain-analysis platforms . Professional certifications such as CFE, CFCS, CAMS, GIAC, or comparable investigative, fraud , financial-crime, cybersecurity, or intelligence credentials . What Success Looks Like Success in this role requires significantly more than knowing how to enter an address into a blockchain analytics platform. The successful candidate should be able to receive a complex transaction, wallet, allegation, or investigative question and independently determine how to trace the activity, which chains and protocols are involved, what the available data establishes, what additional information is needed, what attribution can reasonably be made, and where the technical or evidentiary limitations prevent a definitive conclusion . The individual should be able to move seamlessly between on-chain and off-chain evidence , recognizing that a blockchain transaction may establish movement of assets without necessarily establishing the identity, knowledge, intent, or conduct of the person behind a wallet. They should also be capable of converting a highly technical blockchain investigation into a concise and defensible explanation that an investigator, attorney, executive, regulator, or law-enforcement partner can understand and act upon. At the same time, this person must be sufficiently versatile to apply the same investigative discipline to internal fraud , insider risk, enterprise data, third-party misconduct, and protective-intelligence matters when required. The hierarchy is much clearer this way: blockchain investigations are the specialized core competency; fraud /investigative intelligence is the broader mission; enterprise analytics and PST support are complementary capabilities. That should materially improve the candidate pool versus a title that makes blockchain expertise appear interchangeable with general data analytics. OKX Statement: OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. The salary range for this position is $143,000 - $214,000 The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via OKX internal or external careers site. Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: New York City Workplace: Hybrid About Stepful: Stepful is a workforce platform redefining how America's largest health systems build, train, and retain their talent. Since our founding in 2021, Stepful’s trained over 32,000 practice-ready healthcare workers. Layering onto our successful direct-to-consumer training, Stepful partners with leading healthcare institutions to address the growing national shortage of healthcare workers. We’re improving access to quality healthcare for everyone, everywhere, and improving access to healthcare career ladders for those who need them most. Our students form the talent pipelines for major employers such as NY-Presbyterian, Mt. Sinai, HCA, Providence, CVS, and Walgreens. We have partnerships with half of the top 10 health systems in the US and are in process with many more. Stepful is backed by Y Combinator, Reach Capital, and AlleyCorp, with a recent $55M Series C led by Oak HC/FT https://www.stepful.com/post/stepful-announces-55m-series-c-to-scale-its-ai-powered-training-platform-across-the-healthcare-workforce. We were named the #1 EdTech company in the U.S. by TIME for 2025 https://www.stepful.com/post/stepful-named-1-edtech-company-in-us-top-10-globally-times-2025-list. Our values: We credit much of our success to our exceptional team. We’re looking for mission-driven builders who thrive in fast-paced, ambiguous environments, and embody our four core values: - Care first: We do whatever it takes for our students to succeed. - Learn quickly: We test, learn with data, and iterate. - Build together: We win when we rely on each other. - Own it: We show up, take initiative, and show pride. THE OPPORTUNITY: As more health systems turn to Stepful to build their workforce, the story we tell them has to be sharp, consistent, and backed by proof. We're hiring a Senior Product Marketing Manager to own that story from end to end: how we position Stepful to health system and employer partners, the assets our sales team uses to win deals, the customer stories that prove our impact, and the account-based programs that reach our priority accounts. This is a hands-on, independent role. You'll own the product marketing and B2B content engine day to day, run your own programs without close oversight, and partner on larger go-to-market launches as the function grows. This hybrid opportunity is based out of our NYC office, reporting into the Director, Enterprise Marketing. WHAT YOU'LL DO: Positioning & GTM Resources - Own and maintain Stepful's B2B positioning and messaging, and update it as our programs, partners, and market evolve - Build and refresh GTM assets such as pitch decks, one-pagers, battlecards, and email templates, in partnership with our Workforce Solutions team Content & Customer Proof - Run case study production end to end, from partner interviews and approvals to publishing and distribution - Own the content calendar and keep a steady cadence of content that supports pipeline goals - Partner with Client Success to find partner outcomes worth telling, and with Product and Learning to translate program details into buyer-ready language Demand Gen & ABM - Build and run outbound and ABM sequences in Clay, from account lists and enrichment to personalized multi-touch campaigns, coordinated with sales on target accounts - Own reporting on campaign and content performance, share results on a regular cadence, and use what you learn to decide what to test next - Experiment with AI tools to speed up research, content production, and personalization, and document what works for the team WHAT YOU'LL BRING: - 5+ years of B2B marketing experience across product marketing, demand generation, and/or content, including ownership of positioning and messaging - A track record of building sales enablement assets that sellers actually use, and of partnering closely with a sales team - Experience producing customer case studies and running a content calendar at a steady cadence - Hands-on experience running ABM or outbound programs aimed at enterprise buying committees, including building sequences yourself in Clay or a similar tool - Excellent writing skills: you can make a complex offering clear and compelling for an executive buyer - Comfort with data: you track funnel and campaign metrics, report on them clearly, and use results to change your approach - The ability to manage several workstreams at once with little day-to-day direction, and to flag risks and tradeoffs early BONUS POINTS IF: - You've marketed to health systems, hospitals, or HR and workforce leaders - You've worked in EdTech, workforce development, or healthcare - You've been the first product marketer at a Series B–D startup - You have experience with HubSpot or other marketing automation and CRM tools INTERVIEW PROCESS: - Introductory call with Talent Acquisition team member - Interview with Hiring Manager - Take-Home Assignment - Virtual Panel Interview - On-Site Panel Interview BENEFITS AND COMPENSATION: - Meaningful Equity Stake - Subsidized Medical, Dental, and Vision insurance plan options - 401(k) - FSA, HSA and commuter benefits - Learning stipend - Open vacation policy, including: - Guidance of 15 days PTO annually - Stepful closed the last week of December - 15 work-from-anywhere days - 10 public holidays observed for 2026 The target base salary range for this opportunity is $150,000 - $180,000, and is part of a competitive total rewards package including equity and benefits. Individual pay may vary from the target range and is determined by a number of factors including experience, internal pay equity and other relevant business considerations. Stepful is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran status, gender identity or expression, sexual orientation, pregnancy, or other applicable legally protected characteristic. -- In light of recent hiring scams, if you're selected to move onto the next phase of our hiring process, a member of our Talent Acquisition team will reach out to you directly from an @stepful.com email address to guide you through our interview process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is an unusually demanding distributed system. Training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts, exchange data continuously, and have to keep making progress while hardware fails, load shifts, and the research changes underneath them. How well that system holds together determines how much of our compute turns into learning, and how quickly the team can try the next idea. As a Research Engineer on the Distributed Systems team within RL Engineering, you'll work on whatever part of that system is the current limit. That might be scheduling and placement, data movement between components, running large numbers of sandboxed environments, storage and checkpointing, networking, fault tolerance, autoscaling, or the observability that tells us what a run is actually doing. We're looking for generalists: engineers who can move between these layers, reason from first principles about a system they haven't seen before, and pick the problem that matters most rather than the one closest to their prior experience. Our system changes as fast as the research does, correctness under failure matters as much as throughput, and the best solutions often come from understanding the ML workload well enough to know which guarantees it actually needs. Strong candidates have built and run large distributed systems, care about getting the details right, and want to apply that experience to a workload that is very large, very heterogeneous, and changing quickly. Key responsibilities Design, build, and operate the distributed systems that run RL at scale, across training, sampling, and environment execution Find and remove whatever currently limits the system, whether it's scheduling, data movement, storage, networking, or coordination Build fault tolerance into every layer: failure detection, isolation, and recovery that keep long-running jobs making progress without human intervention Design resource management and autoscaling so that compute follows demand as a run's needs shift Build observability that makes it possible to understand what a run is doing and why it slowed down, stalled, or produced unexpected results Build automation that detects and remediates common problems, and design interfaces that let engineers and automated tools operate runs safely Work with researchers and performance engineers to make sure systems changes preserve training correctness and don't introduce subtle nondeterminism Remove classes of failure at their source through incident review, testing, and redesign, and write clear design documents for what you build Minimum qualifications Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go Experience designing, building, and operating large-scale distributed systems in production Deep understanding of distributed systems fundamentals, including consistency, coordination, consensus, failure modes, and recovery Ability to reason quantitatively about throughput, latency, and resource costs across compute, memory, storage, and network Experience debugging complex failures across many hosts and services, including failures you can't reproduce locally Strong written communication, including design documents and incident writeups Preferred qualifications Experience running ML training or inference infrastructure at scale Experience across several layers of the stack, such as scheduling, storage, networking, and orchestration Experience building schedulers, autoscalers, or resource management systems Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale Experience with high-performance networking, RDMA, or collective communication libraries Experience building observability or automated remediation for large fleets Experience with async Python frameworks such as Trio or asyncio Familiarity with reinforcement learning or large language model training workloads Representative projects Design a scheduler that places training, sampling, and environment work across a heterogeneous cluster while respecting network topology and failure domains Build a failure detection and recovery system that lets a long-running job survive host and network failures with minimal lost work Scale environment execution substantially without increasing tail latency for the training step Design an autoscaling policy that rebalances compute across components as a run's bottleneck shifts Build a diagnostics system that explains why a run's throughput dropped and proposes a fix Trace a rare data corruption bug across many services to a race condition in a recovery path, and redesign the path so the class of bug can't recur Design the operational interface for a run so that automated tools can safely diagnose and adjust it under human oversight The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote-Friendly (Travel Required) | San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Data Center Security Engineering (DCSE) secures Anthropic's data center footprint; this role covers how the sites are designed and built to be secure. Much of that footprint is designed and built with partners, so a site's security is decided early: in what Anthropic hands the people who build it, and in how rigorously the delivered systems are tested against it. You'll design and specify the physical security systems for a site: perimeter and vehicle barriers, intrusion detection, video, security lighting, and the site penetrations and utility entry points that bypass them. Design firms and integrators produce the site drawings and install; you specify, review, and verify. You'll write the performance requirement and verification method behind each control, review every site design against them at each stage with redlines a design team can act on, test in the field that what was built performs as specified, and re-verify post-acceptance changes. This is a foundational role. You'll own Anthropic's physical security reference design package (typical details, reference drawings, schedules, and test procedures) in the form partners build from, and keep it current against each site's threat basis and the sites actually being built. You'll set the technical position for a site and decide what applies where; where a requirement can't be met as written, you'll engineer the compensating control and document the deviation. You'll work with the rest of DCSE, with Anthropic's design, construction, and real estate counterparts, and directly with the vendors who build to the package. We use Claude throughout our engineering workflow and expect you to as well. The same seat covers the team's security operations control rooms. You'll set their design and operational requirements and accept delivered systems against them, working day to day alongside the team's platform engineers, who own the software and compute that run in them. This role involves regular travel to data center sites. These are critical services, and this role participates in an on-call rotation for them. Key responsibilities Produce a vendor-ready design package for perimeter barriers and hostile vehicle mitigation, intrusion detection and its zoning, video coverage, security lighting matched to camera performance, and penetration protection: performance specifications, typical details and reference drawings, and device and zone schedules, written so a design firm can build to them and a test can prove them Define the per-site engineering basis: which requirements apply to a site based on its risk profile and the threats it faces, with compensating controls and documented deviations Write the acceptance criteria and test methods: the verification method behind each requirement and the evidence a site must produce to pass acceptance Set standoff, structural hardening, and site layout criteria for new designs, tied to the threat basis they derive from Run field verification: commissioning and acceptance testing of perimeter, detection, video, and lighting against performance criteria (detection coverage tests, photometric measurements, video quality checks) Write the operational and design requirements for security operations control rooms: console layout, wall versus workstation content, supervisor placement; room network, power, backup, and resilient communications to the team's segmentation and hardening baseline Own control room acceptance: factory and site acceptance criteria written before the build, then accept or reject delivered systems (video wall, consoles, cabling, fit-out) against them Minimum qualifications Have designed or specified physical security systems (perimeter barriers, intrusion detection, video, security lighting) for campus-scale sites: multiple buildings, a secured perimeter, many detection zones Read and produce construction documents (site plans, civil and electrical drawings, device schedules, submittals) using standard design and markup tools such as AutoCAD, Revit, or Bluebeam, and find what is missing as readily as what is wrong Write performance requirements that are testable: each states what must be true, how it will be verified, and what evidence shows it Have run commissioning and acceptance tests against performance criteria and rejected work that did not meet them Derive requirements from a threat basis rather than a product catalog: you can say which adversary a control stops and where the next weakest point is Have owned an engineering domain where you set the approach, chose what applied to each site, worked directly with vendors, and answered for the result Preferred qualifications Experience carrying a physical security design from construction documents through construction to acceptance testing Experience engineering the security scope of colocation or partner-delivered facilities Working knowledge of published standards for standoff, hostile vehicle mitigation, and intrusion detection zoning Photometric and video quality measurement experience Control room, AV, or network design experience: console layouts, video wall systems, resilient communications Experience using AI-assisted tooling for drafting and review as a core part of your workflow The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.