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Location: Remote (US); San Francisco, CA; New York, NY (HQ) 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 We’re hiring a Design Systems Engineer to be one of the few engineers building the components that every Ramp product team uses — the person who makes our design system real in code. You’ll work in close partnership with our design systems lead and designers: they decide what the rules are, and you decide how to enforce them. Sometimes that’s a component that won’t allow a bad pattern. Sometimes it’s a codebase move that makes the right path the easy one. Sometimes it’s automation that catches drift before it spreads. With AI agents now writing much of the UI, this role is also at the frontier of a changing craft. You’ll help decide what the system has to guarantee when humans and agents are both building on top of it — because agents don’t settle for the happy path, and the system needs to hold up either way. Having worked as a designer (or deeply alongside one), you understand the design-eng collaboration challenges firsthand. You’re driven to improve it because you’ve lived with the pain points. You excel in UI and accessible design, prefer working directly in-browser, and get excited about emerging CSS properties. This is an IC role on a small team, which means you’ll have real say in architecture, API design, and the tradeoffs that shape how Ramp builds — foundational, detail-obsessed frontend work with an outsized impact on every screen we ship. What You’ll Do - Build and evolve the components and APIs that every product team at Ramp depends on - Make the enforcement call: when to encode a rule in the component itself, when to leave it to guidance, and when to invest in automation that catches drift - Partner with our design systems lead and designers to turn UX patterns and principles into working, consistent components - Shape the system so it holds up when both engineers and AI agents are building on it - Contribute to internal tooling and infrastructure that keeps velocity high without sacrificing quality - Champion the user experience and accessibility of our products, and keep the quality bar high - Help designers and engineers across Ramp ship faster with elegant, consistent component APIs and a focus on developer experience - Advocate for users by continuously iterating on our core products and experiences - Participate in day-to-day team rituals like design crit, story creation, and weekly stand-ups - Help us hire and grow the team to bring more craft and more perspectives to the work What You Need - Tech/startup or digital product agency experience, or equivalent - A strong frontend engineer who could pass any engineering loop at Ramp — real hands-on skill, not just prompting AI to write code - Experience building design system components and APIs, not only consuming them - Excellent front-end development skills in semantic HTML, CSS (up to date on latest features) and JavaScript (and frameworks, pref. React) - Ability to drive implementation end to end, with sound UX and system design sense - Strong understanding of Product Design software (pref. Figma) and visual/interaction design principles - Strong organizational skills and a love for documentation - Excellent communication and collaboration skills, with a willingness to push back with reasons — e.g., when encoding a rule in a component would slow everyone down - Care for the details: motion, states, accessibility, and the small decisions that make a system feel coherent Nice to Haves - Design systems experience from before AI tooling took off - Ability to articulate complex concepts to technical and non-technical peers - Solid understanding of accessibility development practices 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

Мы в поисках Middle / Middle+ Python Backend Developer. - Коммерческий опыт от 3 лет в backend-разработке, из них от 2 лет с Python;

Location: Remote - US Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Principal, Product Learning & Development About the job Twilio is the world’s leading customer engagement platform empowering developers to build modern communication applications and experiences designed to be trusted, simple and smart. Twilio is looking for a Principal, Product Learning & Development to bring our AI first PDLC vision to life and build the capability our product organization needs to deliver it. Reporting to the Director of Product Strategy & Operations, this role owns how our PMs get better at their craft, and how they learn to do that craft with AI. You'll build the competency model and curriculum that define "how we do product here," then go beyond curriculum by designing and shipping the internal tooling (prompt libraries, agents, PRD generators) that makes a PM measurably faster and sharper. You'll bring our AI first PDLC vision to life, partnering with product and engineering leaders to find where AI genuinely changes the work, and coaching the org through the change. Responsibilities We are looking for a leader who brings product, learning, and hands on AI expertise to help: Design and deliver the PM Academy, covering onboarding and ongoing curriculum across PRD writing, discovery, prioritization, roadmapping, and stakeholder influence, each taught with AI in the workflow. Design and help build and facilitate adoption of "PM in a box": ship internal AI tooling such as prompt libraries, agents, and PRD and research generators, as products with users, feedback loops, and adoption targets. Bring the AI first PDLC vision to life and execute against it, partnering with Product leaders to map current workflows and identify the AI and automation opportunities worth pursuing. Run cohort programs for new PMs and newly promoted PM managers, and design tailored programming for different parts of the organization rather than one generic track. Curate the internal playbooks, templates, and documentation that carry "how we do product here," and keep them current as practice changes. Facilitate workshops, office hours, and 1:1 coaching for PMs and PM leaders, building the credibility to coach senior people. Drive AI adoption across the PM org through a champion network that surfaces use cases from inside each team. Measure impact against baselines captured before rollout. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! Required: Bachelor’s degree in Business, Computer Science, a related field or equivalent practical experience. 8+ years of experience across product management, consulting, program management, L&D or enablement Experience leading programs or product operations for B2B SaaS, PaaS or equivalent Outstanding written and verbal communication that drives executional impact at scale, distilling complex detail into an executive narrative, and explaining technical concepts to audiences without technical backgrounds. Strong facilitation, and the ability to build trust and exchange ideas across organizational boundaries in service of a broader goal. Excellent problem solving and organizational skills. Ability to thrive in a fast paced, evolving, ambiguous environment, with a default to action in order to adapt quickly to changing priorities and requirements. Desired: Master’s in computer science or engineering or business administration Hands on experience building AI agents, automated workflows, and internal tooling. Experience leading change management in B2B SaaS Location This role will be remote and based in the USA. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, approximately 5-10% travel is anticipated to help you connect in-person in a meaningful way. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. The estimated pay ranges for this role are as follows: Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $171,120 - $ 213,900 Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $181,200 - $226,500 Based in the San Francisco Bay area, California: $201,280 - $251,600 This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave. The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Applications for this role are intended to be accepted until March 1, 2027, but may change based on business needs. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We're hiring a Senior Business Assistant to join our Office of the CFO team, based in London. In this role, you’ll support the CFO in key leadership, board, and finance meetings by preparing materials in advance, documenting decisions and actions, and coordinating follow-through afterwards. It's a content-focused role: you'll need a genuine working understanding of finance to follow the discussion, not just log who said what. WHAT YOU’LL DO Meeting Support & Follow-Through - Join key meetings: Join meetings alongside the CFO — leadership, board, and finance-function meetings — capturing accurate notes and the decisions that come out of them. - Own the follow-up: Turn discussions into clear, assigned action items and drive them to completion, chasing owners and flagging slippage before it becomes a problem. - Track outstanding items: Maintain a live view of open actions and decisions across the CFO's meeting cadence, escalating blockers to the CFO directly. Pre-Meeting Preparation - Prepare pre-reads: Prepare pre-reads, briefing packs, and agendas ahead of key meetings, pulling together relevant background, data, and context. - Coordinate stakeholder input: Coordinate input from stakeholders across Finance — Controllership, Tax, Treasury, FP&A — so the CFO walks in fully briefed. - Anticipate what's needed: Proactively anticipate what the CFO will need for a given meeting, rather than waiting to be asked. Finance-Literate Business Support - Follow technical discussions: Apply a working understanding of financial concepts and terminology to accurately capture and summarise technical finance discussions. - Sanity-check materials: Review financial reports, decks, and models before they reach the CFO, spotting errors, inconsistencies, or omissions. - Partner across finance: Partner with Controllership, Tax, Treasury, and FP&A to gather the input and context needed for meetings and follow-ups. Communication & Organisation - Produce clear meeting notes: Produce clear, well-structured meeting notes and summaries, distributed promptly to attendees. - Maintain a master tracker: Maintain a single source of truth for action items, decisions, and deadlines across the CFO's meeting cadence. - Handle information with discretion: Manage confidential and sensitive business and financial information with sound judgement. WHAT WE’RE LOOKING FOR - Proven experience as an EA, business assistant, or similar role supporting senior executives, ideally within a finance function. - A working understanding of financial concepts and terminology (P&L, budgeting, forecasting) sufficient to follow and accurately summarise finance discussions. - Excellent note-taking and written communication skills, able to turn meeting discussions into clear, actionable outputs. - Strong organisational skills, with a proven ability to track and drive multiple action items to completion. - Comfortable preparing pre-meeting materials, pulling together data and context from multiple stakeholders. - High level of discretion when handling confidential business and financial information. - Proactive, detail-oriented, and comfortable operating in a fast-paced, high-growth environment. - Strong proficiency with everyday productivity tools (Microsoft Office / Google Workspace). - Bachelor's degree in finance, business, or a related field is a plus. - Experience supporting a CFO or finance leadership team specifically is a strong plus. - Experience in a venture-backed, high-growth startup or scale-up is a plus. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: Dublin, Dublin, Ireland From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role As Fivetran scales its Enterprise business, we're looking for a senior individual contributor – with a strong bias towards AI automation – to own the International Demand Generation across EMEA and APAC. You'll be the right hand to the Director of Global Enterprise Demand, driving lead generation to ensure we have the touchpoints and MQL volumes needed to hit Enterprise sales targets. You’ll build and run the always-on 1-to-many ABM engine for Enterprise accounts in EMEA and APAC: agent-driven workflows that turn account signals (intent, tech stack, CRM stage) into campaigns, creative, and landing pages. This is a strategy-and-execution role: you'll set the plan and roll up your sleeves with the team to make it work. Location and work model: In person in Dublin, Ireland. What You’ll Do You'll co-own the EMEA and APAC enterprise pipeline number alongside the EMEA marketing team, with accountability for lead generation, territory hydration, and the touchpoint and MQL volumes needed to support sales targets. You'll execute account-specific programs to drive account engagement, lead generation and monitor the funnel from touchpoints through qualified opportunities and pipeline. You will own key paid channels, like LinkedIn and Meta, to drive these outcomes. Things you will build: Agentic workflows, using Claude or similar harnesses, that creates, launches, and optimizes LinkedIn and Meta campaigns across target-account tiers. Connections between ad platforms, Salesforce, and signal sources such as intent and tech-stack data, so audiences and creative update without manual list uploads. A weekly review loop where the system and you assess what worked and improve it. You'll work across lifecycle marketing, customer marketing, ABM, product marketing, and regional teams to orchestrate integrated programs. Partnering with the Director of Global Demand and Regional Marketing and ABM leaders, you'll improve the demand operating model across EMEA and APAC. What success looks like 6 months: target-account tiers and signals defined; an agent-assisted campaign workflow live for a first segment, with measurable gains in launch speed and cost per touchpoint or MQL. 12 months: the engine runs across the EMEA and APAC Enterprise account list with BDR handoff, and it improves itself through a regular review loop. Pipeline influence and BDR conversion on engaged accounts are tracked. Skills We’re Looking For Deep, hands-on expertise in paid media and account-based marketing for enterprise buyers (LinkedIn required), plus experience in at least one of lifecycle, customer, or product marketing. Experience running multi-lifecycle stage campaigns targeting enterprise buying committees Proficiency in using LLM harnesses to automate marketing tasks, and improve marketing performance Strong business judgment and a clear point of view, with the confidence to challenge senior stakeholders constructively and build alignment around difficult tradeoffs. Excellent communication skills, specifically in communicating business outcomes, headwinds and tailwinds You’ve built and shipped agentic or automated workflows in production, not just prompts: connecting APIs or MCP servers, defining guardrails, and measuring impact. Hands-on familiarity with CRM data (Salesforce), ad platform APIs, and signal tools is a strong plus. You're comfortable operating as a senior IC who leads through influence rather than headcount. You should be comfortable galvanizing support behind an initiative when a number is at risk. You think in systems, you're fluent in the metrics that matter, and you move fluidly between setting strategy and executing the work yourself. #LI-LA1 #LI-HYBRID The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role. Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Pay Range €99.552 — €124.440 EUR Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Location: London, England, United Kingdom From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role As Fivetran scales its Enterprise business, we're looking for a senior individual contributor – with a strong bias towards AI automation – to own the International Demand Generation across EMEA and APAC. You'll be the right hand to the Director of Global Enterprise Demand, driving lead generation to ensure we have the touchpoints and MQL volumes needed to hit Enterprise sales targets. You’ll build and run the always-on 1-to-many ABM engine for Enterprise accounts in EMEA and APAC: agent-driven workflows that turn account signals (intent, tech stack, CRM stage) into campaigns, creative, and landing pages. This is a strategy-and-execution role: you'll set the plan and roll up your sleeves with the team to make it work. Location and work model: Hybrid in London, UK. What You’ll Do You'll co-own the EMEA and APAC enterprise pipeline number alongside the EMEA marketing team, with accountability for lead generation, territory hydration, and the touchpoint and MQL volumes needed to support sales targets. You'll execute account-specific programs to drive account engagement, lead generation and monitor the funnel from touchpoints through qualified opportunities and pipeline. You will own key paid channels, like LinkedIn and Meta, to drive these outcomes. Things you will build: Agentic workflows, using Claude or similar harnesses, that creates, launches, and optimizes LinkedIn and Meta campaigns across target-account tiers. Connections between ad platforms, Salesforce, and signal sources such as intent and tech-stack data, so audiences and creative update without manual list uploads. A weekly review loop where the system and you assess what worked and improve it. You'll work across lifecycle marketing, customer marketing, ABM, product marketing, and regional teams to orchestrate integrated programs. Partnering with the Director of Global Demand and Regional Marketing and ABM leaders, you'll improve the demand operating model across EMEA and APAC. What success looks like 6 months: target-account tiers and signals defined; an agent-assisted campaign workflow live for a first segment, with measurable gains in launch speed and cost per touchpoint or MQL. 12 months: the engine runs across the EMEA and APAC Enterprise account list with BDR handoff, and it improves itself through a regular review loop. Pipeline influence and BDR conversion on engaged accounts are tracked. Skills We’re Looking For Deep, hands-on expertise in paid media and account-based marketing for enterprise buyers (LinkedIn required), plus experience in at least one of lifecycle, customer, or product marketing. Experience running multi-lifecycle stage campaigns targeting enterprise buying committees Proficiency in using LLM harnesses to automate marketing tasks, and improve marketing performance Strong business judgment and a clear point of view, with the confidence to challenge senior stakeholders constructively and build alignment around difficult tradeoffs. Excellent communication skills, specifically in communicating business outcomes, headwinds and tailwinds You’ve built and shipped agentic or automated workflows in production, not just prompts: connecting APIs or MCP servers, defining guardrails, and measuring impact. Hands-on familiarity with CRM data (Salesforce), ad platform APIs, and signal tools is a strong plus. You're comfortable operating as a senior IC who leads through influence rather than headcount. You should be comfortable galvanizing support behind an initiative when a number is at risk. You think in systems, you're fluent in the metrics that matter, and you move fluidly between setting strategy and executing the work yourself. #LI-LA1 #LI-HYBRID The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role. Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Pay Range £96,398 — £120,497 GBP Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Задачи: проектировать и владеть end-to-end аналитическими процессами в Amazon Redshift — сложный многошаговый SQL (оконные функции, CTE, масштабные join'ы, оптимизация производительности); проводить глубокий анализ поведения игроков — сегментация, RFM-моделирование, когортный анализ, прогнозирование LTV и churn;

Location: Remote Ireland; Remote, Austria; Remote, France; Remote, Germany; Remote, Netherlands; Remote, Spain; Remote, United Kingdom GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role GitLab’s Forward Deployed Engineering team is a field-situated product engineering function focused on strategic customer outcomes, artificial intelligence (AI) adoption, and direct contributions to GitLab’s product. This isn't a traditional field engineering, solutions architecture, or professional services role. As a Staff Forward Deployed Engineer, you'll work closely with customers while maintaining the technical standards and contribution discipline of a Staff-level product engineer. You'll work where strategic customer urgency, complex technical ambiguity, and GitLab product execution intersect. You'll partner directly with strategic customers and teams across Product, Engineering, Support, Site Reliability Engineering (SRE), Solutions Architecture (SA), Customer Success Architecture (CSA), Customer Success Management (CSM), and Professional Services. You'll diagnose and resolve high-impact adoption blockers, contribute production-quality fixes and features, and turn what you learn into repeatable patterns for GitLab and its customers. Why this role exists Strategic customers sometimes encounter challenges that are too broad, deep, urgent, or cross-functional for any single team to own from start to finish. These challenges may involve product gaps, performance degradation, scale bottlenecks, AI governance, adoption blockers, architectural constraints, Git usage patterns, continuous integration and continuous delivery (CI/CD) complexity, application programming interface (API) automation, security requirements, or operational instability. Forward Deployed Engineering provides technical stewardship in these moments. The team doesn't simply observe, report, or escalate. You'll engage directly, diagnose the underlying technical problem, collaborate with the right teams, contribute code or technical solutions where appropriate, and transition the outcome into normal ownership once the customer is stable and the learning can be reused. What you’ll do Product contribution Contribute production-quality code to GitLab’s product and adjacent systems. Develop bug fixes, features, integrations, tooling, and performance improvements when strategic customer outcomes require direct engineering work. Work within GitLab’s product and engineering processes, including issue discovery, merge request creation, testing, review, documentation, and maintainability. Partner with Product and Engineering so customer-driven solutions support long-term product direction rather than becoming one-off customizations. Turn blockers discovered in the field into durable product improvements, reference architectures, documentation, and repeatable implementation patterns. Strategic technical stewardship Engage with strategically important customers when adoption, retention, executive confidence, or public trust is materially at risk. Diagnose complex problems across GitLab product behavior, customer architecture, Git internals, CI/CD workflows, API usage, observability, infrastructure, networking, and cloud environments. Coordinate across Product, Engineering, SRE, Support, SA, CSA, CSM, Professional Services, and customer technical teams to drive resolution from discovery through handoff. Provide recommendations grounded in data, traces, and systems analysis to improve GitLab usage, workflows, automation, and architecture. Create durable outcomes without establishing permanent dependency on Forward Deployed Engineering. AI adoption and agentic software development lifecycle Drive governed, measurable, and production-oriented adoption of GitLab Duo Agent Platform with strategic customers. Identify and resolve AI adoption blockers involving governance, usage controls, auditability, security, compliance, operating models, workflow design, and integrations. Develop customer-safe adoption patterns for the agentic software development lifecycle (SDLC), AI-assisted development, intent-based review, AI governance, and human-in-the-loop software delivery. Partner with Product, Engineering, Field, and Customer Success teams to turn AI adoption learning into reusable guidance and product improvements. Thought leadership Create technical narratives grounded in customer experience and product reality that can help shape the industry’s approach. Contribute to Well-Architected Frameworks, whitepapers, webinars, reference architectures, technical strategy memos, and adoption frameworks. Guide ideas through discovery, formulation, validation, amplification, and adoption across GitLab. Partner with SA, CSA, Product, Engineering, Marketing, Product Marketing Management, CSM, Support, and executive stakeholders to make technical thought leadership a shared company capability. What you’ll bring Staff-level experience building, operating, or improving complex production software systems. Experience contributing to large, mature product codebases with high standards for testing, maintainability, performance, and security. Strong Ruby on Rails or Go experience and the ability to contribute directly to GitLab’s product and adjacent systems. Experience with AI-assisted software development, agentic workflows, AI governance, model evaluation, context management, prompt and workflow design, or AI adoption in enterprise environments. Experience diagnosing complex system behavior across application code, data stores, infrastructure, observability, networking, APIs, and customer usage patterns. Deep knowledge of modern DevSecOps workflows, including Git, merge requests, CI/CD, security controls, compliance needs, and enterprise software delivery. Experience working with strategic customers or senior technical stakeholders in ambiguous, high-impact situations. The ability to coordinate across product, engineering, field, and customer teams without formal authority. Strong written communication and sound judgment, including the ability to create technical narratives and distinguish reusable product work from customer-specific customization. Strongly preferred qualifications Direct experience with GitLab as a platform, including GitLab.com, GitLab Dedicated, or GitLab Self-Managed. Production experience with Ruby on Rails, Go, PostgreSQL, Redis, Sidekiq, Vue, TypeScript, Kubernetes, Docker, Linux, or observability tools. Deep familiarity with Git internals, repository performance, large-scale Git usage patterns, or GitLab Runner behavior. Experience creating technical thought-leadership materials, such as whitepapers, technical talks, architecture frameworks, requests for comments, public technical writing, or internal strategy documents. A background in performance engineering, site reliability engineering, platform engineering, infrastructure engineering, or distributed systems. Experience working in open source or highly asynchronous engineering environments. Technologies and domains Directly relevant technologies and domains include: Ruby on Rails Go AI-assisted development and the agentic SDLC PostgreSQL Redis and Sidekiq Git internals GitLab CI/CD and Runner architecture Kubernetes and containers Terraform Linux, networking, observability, and performance analysis Vue and TypeScript APIs and automation DevSecOps governance, security, and compliance What this role is not This role isn't: A generic field engineering role. A proof-of-concept factory. A replacement for Solutions Architecture, Customer Success Architecture, Customer Success Management, Professional Services, Support, SRE, Product, or Engineering. A customer-specific customization function. Unbilled Professional Services. A requirements-gathering role that only escalates to Product. An AI evangelism role disconnected from product execution. Success measures Success in this role may include: Stabilizing strategic customer adoption or retention risks. Fixing product bugs or contributing features. Removing AI adoption blockers for strategic accounts. Creating reusable implementation patterns and transitioning them to long-term owners. Producing or enabling Well-Architected Frameworks, whitepapers, webinars, or technical narratives. Resolving cross-functional customer challenges without creating permanent dependency on Forward Deployed Engineering. Equipping Product, Engineering, Support, CSA, CSM, Professional Services, and SA teams with better guidance based on learning from the field. Increasing adoption and effective use of GitLab capabilities, especially GitLab Duo and GitLab Duo Agent Platform, in targeted accounts. About the team The Forward Deployed Engineering team connects strategic customer needs with GitLab product execution. The team works directly with customers and across GitLab to resolve complex adoption challenges, contribute durable product improvements, and create reusable technical guidance. Its goal is to stabilize urgent situations, improve the product, and transition ongoing ownership to the appropriate team rather than create a permanent dependency. Ideal candidate profile You're a Staff-level product or platform engineer who can operate in the field without becoming field-only. You're comfortable reading traces, writing production code, debugging architecture, discussing AI governance, leading a customer technical session, opening a merge request, outlining a whitepaper, and coordinating across teams to achieve a strategic customer outcome. You're not simply a strong communicator with technical awareness. You're a credible engineer with the judgment, presence, and narrative ability to turn customer reality into product contributions, adoption guidance, and company-level thought leadership. We welcome candidates with different backgrounds and levels of experience. Many successful candidates don't meet every qualification. If you're excited about this role, we encourage you to apply and let our recruiting team assess your application. How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: New York City, NY Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: Reddit has a flexible-first workforce. Don't live near our New York office? No worries: you can work remotely from anywhere on the US East Coast (Eastern Time). The Ads Foundational Representations (AFR) team develops signals and representations of Reddit’s core entities (ads, posts, users, and so on), capturing the semantic, contextual, and behavioral information that Reddit Ads needs. We work on building embeddings to understand content and users' interests based on the content they engage with. Our team has the potential to highlight one of Reddit's biggest differentiators: genuinely curated, high-quality, extremely relevant, and daily updated organic content. We are a Machine Learning/Data heavy team with a focus on the following areas: Multimodal & Content Embeddings - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) text and media content by embedding them into a shared space. Contextual and Behavioral Relevance - Working with Product & Data Science, establishing definitions of what ads are relevant to users and the content we show them next to, building metrics and fine-tuning embeddings to better reflect relevance. Knowledge Graph Embeddings - Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting & business insights. User Intent Modeling - Leveraging various techniques to introduce user representations based on the content they interact with: batch & real-time sequence modeling, LLM summarization, etc. LLM-based Representations - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes The signals and features we create become a key piece in the Ads Delivery funnel, from targeting to the auction, as well as the Business Insights product and other advertiser-facing products such as Creative generation and optimization. As a Staff ML Engineer , you’ll be in charge of setting the technical direction of multiple pillars the team owns. You will lead cross-functional ML projects end to end - from high-level business gap analysis to engineering execution. Roughly 50% of your time will be spent on technical leadership and mentorship (driving strategy & designs, cross-functional collaboration, raising the quality bar), another 50% being individual hands-on work (data analysis & engineering, modeling & automation). Responsibilities Providing technical leadership and mentorship to MLEs in the team: driving designs & their review, establishing best practices in analysis, modeling and engineering, keeping the bar high. Working closely with team/org leadership developing technical strategy for content-based embeddings & relevance for Ads. Developing new or iterating on existing embedding models for advertising use cases, ranging from aggregation pipelines to two-tower architectures and sequence models. Working with local and 3rd-party LLMs/VLMs: extract representations, develop evaluation methodologies, prompt tune and fine-tune large models to build state-of-the-art embeddings. Building data processing and inference pipelines for the models we develop. Qualitative and quantitative evaluation of the various features we develop, end-to-end experimentation from internal benchmarks to downstream recommender system offline metrics to online experiments. Ensuring the reliability, scalability, and performance of the ML systems by writing automated tests, monitoring performance, and implementing best practices for model management. Participating in modeling and coding reviews: You will review work by other team members and provide feedback to ensure that it meets the team's standards for quality and performance. Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions. Required Qualifications: 7+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models. Demonstrated Staff-level technical leadership: mentoring engineers, driving standards and bar raising, leading complex cross-functional projects: from requirements, design to cross-team/functional alignment and execution without direct people-management authority. Excellent communication skills, with the ability to translate complex technical concepts to different audiences, both verbally and in writing. Strong track record of working on content rich NLP/CV problems at scale, and using embeddings as a tool to solve them. Established data-driven approach for ML system development. Excitement about working with data and readiness to look behind the metric numbers. Familiarity with the Ads domain and/or Search/Recommender systems. Experience with mainstream DL frameworks: PyTorch or TensorFlow. Preferred Qualifications: Experience with our stack (Python, Pytorch, Airflow, BigQuery, Ray, k8s, kafka, GCP) Tech leadership experience: mentoring junior engineers and leading complex projects. Hands-on experience with using/fine-tuning/building LLMs. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $230,000 — $322,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Задачи: — Создание безопасной среды для работы коллег с AI. — Помощь в запуске проектов на серверах компании, Yandex Cloud и Yandex AI Studio. — Адаптация AI-решений под глобальные модели. — Работа с open-source моделями: выбор, расчёт оборудования, настройка и поддержка сервиса. — Автоматизация рутинных задач с AI-ассистентами. — Проведение воркшопов и консультаций, подготовка внутренних тренеров. — Оценка AI-решений головного офиса совместно с бизнес-владельцами. — Создание прототипов и пилотов с интеграцией в корпоративные системы. — Техническое взаимодействие с агентствами и интеграторами: требования, проверка архитектуры, приёмка работ. — Проверка безопасности и соответствия требованиям закона о персональных данных (152-ФЗ). — Отчётность и обмен успешными решениями с головным офисом и другими странами. Требования: — Опыт коммерческой разработки не менее 5 лет, знание Python. — Опыт разработки backend-сервисов, API и интеграций в продакшене с использованием REST, SQL, Git, Linux. — Минимум 2 года разработки бизнес-инструментов на LLM, включая промпт-инжиниринг, tool calling, агентов, RAG, эмбеддинги и векторные базы данных. — Опыт развёртывания и эксплуатации open-source LLM на собственных серверах с использованием vLLM, Ollama или llama.cpp, включая расчёт оборудования и квантизацию. — Практический опыт работы с Yandex Cloud и Yandex AI Studio: API, SDK, Model Gallery, эмбеддинги, сервисные аккаунты, API-ключи, логирование данных, Compute Cloud, Serverless Containers, Object Storage. — Опыт переноса LLM-решений между провайдерами (OpenAI, Anthropic Claude, Google Gemini) и собственными моделями с оценкой качества. — Интеграция и автоматизация с использованием MCP-серверов и командной строки на Python, Bash или PowerShell. — Развёртывание и эксплуатация внутренних веб-сервисов на собственных серверах и в Yandex Cloud с Docker, Docker Compose, SSO, логированием, мониторингом и резервным копированием. — Ежедневная работа с AI-ассистентами (Cline, Claude Code, Codex, Cursor), включая агентов в командной строке и ревью кода. — Управление безопасностью: доступ, секреты, защита от prompt injection и утечек данных. — Знание закона о персональных данных (152-ФЗ). — Достижение бизнес-решений с измеримым эффектом и понятной стоимостью эксплуатации. Условия: — Оклад и бонусы. — Сим-карта, ДМС со стоматологией с первого дня, питание (завтрак, обед, ужин). — Скидка на корпоративную продукцию после испытательного срока. — Гибкое начало и окончание рабочего дня. — График работы full-time в офисе. — 5 дополнительных дней отпуска в год. — Оформление в штат аутсорсинговой компании.

We are growing and looking for a full-time, remote Middle Product Manager to define product strategy, identify customer and business needs…. We are growing and looking for a full-time, remote Middle Product Manager to define product strategy, identify customer and business needs and transform them into clear, actionable product requirements.

Location: Cyprus; Finland; Ireland; Malta; Montenegro; Sweden What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: European Union What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: Estonia; Greece; Latvia; Lithuania; Poland; Slovakia; Ukraine What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: United Kingdom - Remote Chainguard is the trusted source for open source. By delivering hardened, secure, and production-ready builds of all the open source software engineers and AI agents rely on, Chainguard helps organizations build faster, stay compliant, and eliminate risk. Our customers include Fortune 500 enterprises and global industry leaders, including Anduril, Canva, Fortinet, Hewlett Packard Enterprise, OpenAI, Snap Inc., and Snowflake. Chainguard is venture-backed by leading investors, including Amplify, IVP, Kleiner Perkins, Lightspeed Venture Partners, Mantis VC, Redpoint Ventures, Sequoia Capital, and Spark Capital. This role, in a nutshell: Our international business has moved past the proving stage. The teams, the sales motion and the early wins are in place across EMEA, but still very much being built out in META (Middle East and Africa) and APJ. The operational foundation now needs to scale with them. We are hiring a Senior Revenue Operations Manager to be the hands-on operator behind planning, forecasting, territory design, reporting and process quality for these regions. This is an individual contributor role with a broad remit. You will work directly with regional sales leadership, report into the Senior Director of Revenue Operations EMEA, and apply global standards and systems to the realities of selling across multiple countries, segments and time zones. You will also be the person who raises it when a global standard does not fit a region, with a proposal for what to do about it. What you will do Planning and territory design Support annual and in-year territory design for EMEA, META and APJ, using account potential, segment, language, legal entity and market maturity to build territories that are equitable and defensible. Support capacity and coverage modeling: headcount plans, ramp assumptions, quota allocation and productivity targets tied to the company financial plan. Set different assumptions for markets at different stages, such as an established EMEA business and an earlier-stage APJ business. Support sales compensation execution with global Sales Operations and Finance, including plan rollout, quota letters and accurate, on-time attainment reporting. Forecasting and reporting Support in running the forecast cadence for the regions you support: weekly pipeline inspection, forecast calls, roll-up accuracy and the written narrative for global sales and finance leadership. Drive the operating reporting rhythm: weekly performance, monthly business reviews, QBRs and regional inputs to Board materials. Own pipeline health and funnel analytics, including conversion by stage, segment, region and country, source and campaign contribution, and win/loss patterns. Identify what is driving each result and recommend what to change. Partnership with regional leadership Act as the revenue operations partner to regional sales leaders and their teams, joining leadership meetings and QBRs with data and recommendations that support fast decisions. Support leaders at different levels of business maturity and with different priorities, and give each the same standard of analysis and attention. Serve as one of the EMEA, META and APJ voices within global Revenue Operations, and keep regional requirements visible in global planning. Systems, data and process Maintain data integrity in Salesforce and the wider GTM stack, including account ownership, hierarchy, segmentation and the reporting fields that executive reporting depends on. Work with global GTM Operations on system and process changes, making sure regional needs are represented without fragmenting the global architecture. Maintain rules of engagement across regions, segments and teams, and resolve coverage and credit questions fairly and promptly. Bring region-specific requirements into process and reporting design, including data residency, GDPR and APAC privacy regimes, and local entity and currency considerations, working with Legal and Finance. Partner with Marketing, BDR, Customer Success, Finance and Legal to remove friction from the regional go-to-market process. What we are looking for Required 7+ years of Sales, Revenue or GTM Operations experience in high-growth Enterprise B2B SaaS. Experience with multi-country territory design, quota allocation and capacity planning. EMEA experience is essential, and exposure to META or APJ is a strong plus. Expert-level Salesforce skills, including reporting, data models and process design, and sound judgment about what belongs in the CRM and what does not. A record of running a forecast process that sales leaders trust, with measurable improvement in forecast accuracy. A strong analytical foundation: you can break an ambiguous problem into its parts and reach a recommendation you can defend. Clear communication across levels, from a front-line manager's pipeline question to an executive summary, without changing the underlying facts. Experience as a trusted operations partner to senior revenue leaders, including giving them unwelcome news when the numbers call for it. Comfort working inside a globally managed function: adopting global standards, pushing back where they do not fit, and avoiding regional fragmentation. Working knowledge of the modern GTM stack (for example Salesforce, Outreach, Gong, HubSpot, CPQ, and Sigma, Tableau or Looker) and the ability to learn new tools quickly. Comfort with international complexity: multiple currencies, legal entities, languages and privacy regimes, and a working day that spans several time zones. Willingness to travel across the regions and to the US for QBRs and planning cycles (1 - 2x per quarter) Nice to have Experience supporting public sector or regulated-industry go-to-market teams. SQL skills or experience building data models directly. Experience mentoring or informally leading analysts or junior operations staff. How success is measured Forecast accuracy improves and leadership relies on the regional roll-up. Territories and quotas are in place on time each planning cycle, with few disputes after launch. Regional leaders get reporting and recommendations without having to ask for them. Salesforce data in the regions meets agreed hygiene standards. Regional requirements are reflected in global system and process decisions. Base Salary Range £129,144 — £152,152 GBP About Us We live and breathe our company values: We are customer obsessed — We focus on delivering solutions to our customers that create value and make their lives better. We have a bias for intentional action — We prioritize, plan, try things, and fail fast. We don't take ourselves too seriously (but we do serious work) — We are solving an important problem which takes focus, but we also like to enjoy the journey. We trust each other and assume good intentions — We're transparent with decisions to empower team members to make well informed decisions. A few of the benefits we offer: Flexible & Remote-First Culture: Work remotely with team meetup opportunities, bi-annual destination summits, and a monthly stipend for coworking spaces, phone and internet costs. Our Approach to Equity: Receive stock options upon hire and promotion. Plus, you can participate in secondary offerings and have 10 years to exercise your options (yes, you read that correctly: 10 years!). 100% Covered Health Insurance: We cover 100% of your health, vision and dental insurance premiums for you and your dependents. Nothing comes out of your paycheck. ∞ Flexible Time Off: Take the time you need – to do our best work, we need to recharge and reset. 18 Weeks Paid Parental Leave: We offer 18 weeks for birthing parents and 12 weeks for non-birthing parents, with the option to use it all at once or throughout your child's first year. If your experience is close but doesn't fulfill all requirements, please apply. We're building the best team in technology and are focused on hiring "Chainguardians" with unique backgrounds, perspectives, and experiences. Chainguard is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. By submitting your application, you acknowledge that Chainguard will process your personal data in accordance with Chainguard's Global Candidate Privacy Notice . ©2026 Chainguard. All Rights Reserved.

Location: Москва Наша команда (70+ человек) создает технологический фундамент для внедрения GenAI в экосистему банка. Мы разрабатываем RAG-платформу, фреймворк исполнения агентов и системы обработки неструктурированного контента (документы, коммуникации). Наши сервисы оборачивают базовые LLM в готовые интерфейсы, позволяя бизнесу быстро создавать собственных агентов и GenAI-приложения. Мы обеспечиваем полный цикл разработки (E2E): ML-инженеры и бэкенд-разработчики работают вместе над реализацией сервисов, в связке с фронтендом и дизайнерами. У нас есть собственная команда разметки для оценки качества и сбора датасетов, с помощью которых мы дообучаем доменные модели под банковские сценарии. Масштаб задач: Сейчас в портфеле более 200 реализованных сценариев. В планах — реализация еще 300+ сценариев, включая создание слоя процедурной памяти для агентов, специализированных поисковых агентов и систем автоматической оценки качества GenAI (Auto-Eval). Развитие Self-Service инструментов (песочниц с UI), где команды банка могут тестировать гипотезы перед интеграцией. Чем предстоит заниматься Мы ищем инженеров, которым интересно не только R&D, но и создание полноценных продуктовых систем, способных обучаться на пользовательском фидбэке и решать конкретные бизнес-задачи. Обязанности * развитие GenAI сервисов: Создание и улучшение RAG-систем (в т.ч. Agentic RAG), инструментов Agent Observability, сервисов обработки документов * обучение моделей: тренировка и дообучение мультимодальных моделей на русском языке (OCR, Embeddings, Rerankers, VLM) * MLOps и Data Management: организация и автоматизация процесса разметки данных (от сбора до контроля качества краудсорсинга) * развитие автономных пайплайнов улучшения качества моделей с использованием LLM-as-a-Judge * Engineering: релиз новых моделей и сервисов в продуктовые среды. Требования * глубокое понимание LLM: опыт работы с большими языковыми моделями, Prompt Engineering, Fine-tuning LLM/VLM * инженерная культура: уверенное владение Python 3, знание ООП, принципов SOLID. Хорошее знание алгоритмов и структур данных. * LLM Stack: опыт работы с LangChain, LlamaIndex или другими фреймворками для разработки агентов и мультиагентных систем (MAS) * Vibe Coding: умение автоматизировать собственные рутинные процессы с помощью AI-инструментов * Mindset: желание постоянно изучать новые SOTA-подходы, модели и технологии * опыт руководства командой ML-инженеров. **Будет плюсом** * активный профиль на GitHub с качественным кодом * достижения (медали) на Kaggle * участие в Open-Source проектах, связанных с LLM/NLP. Условия * комфортный современный офис - м. Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты, годовой бонус * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера * корпоративная пенсионная программа.

Location: San Francisco; New York City In 2026, we launched Computer, the defining product for the new era of agentic AI. We’ve scaled beyond the millions of people using Perplexity every day for research, shopping, investing, and curiosity into a new paradigm of using AI to transform knowledge into action. Thousands of attorneys, Am Law firms, and corporate legal teams already rely on Perplexity every week—and Legal is one of our highest-conviction enterprise verticals. Following the playbook that scaled Perplexity Finance, we are looking for an entrepreneurial Product Manager to build and scale our Legal vertical from the ground up. Product Managers at Perplexity work closely with design, engineering, research, and go-to-market teams to turn frontier AI capabilities into indispensable daily workflows. Whether you have a couple of years of product experience at a legal AI or B2B software company, or you are an early-career builder or operator with high agency and a steep trajectory, this role offers rare end-to-end ownership of a flagship vertical. In your application, please highlight a product, workflow, or agent system you’ve built—or a specific legal problem you believe AI is uniquely positioned to solve. THE ROLE Legal work sits at the exact intersection where Perplexity shines: high-stakes research, multi-document synthesis, verifiable citations, and multi-step execution across specialized systems. Winning in Legal requires clearing an uncompromising bar for accuracy, source authority, document fidelity, and enterprise governance—without sacrificing the speed and simplicity that make Perplexity magical. Sitting within our AI Capabilities & Verticals PM team, you will be the dedicated product owner for Perplexity’s Legal vertical. Rather than building an isolated point solution, you will shape how core Perplexity surfaces—Computer, Search, Teammates, Projects, Plugins, Skills, and Artifacts—come together into a cohesive, trusted experience for litigators, transactional counsel, and in-house legal teams. You will partner across Engineering, Design, AI Research, Partnerships, Sales, and Product Marketing to close product and data gaps, co-design with leading law firms and legal departments, and scale Legal into one of Perplexity’s flagship enterprise businesses. WHAT YOU’LL DO - Own the Legal vertical roadmap end-to-end: Define and execute product strategy across litigation research, M&A and transactional diligence, contract review and drafting, and in-house legal workflows—translating attorney pain points into modular capabilities that benefit the entire platform. - Ship core legal primitives and entrypoints: Partner with Engineering and Design to build the product surfaces high-stakes legal work demands—including structured multi-document review tables for diligence and discovery, passage-level inline citations with side-by-side source verification across PDFs/DOCX/spreadsheets, precision redlining and document comparison, and seamless workflows inside Microsoft Word, Outlook/email, and Slack. - Expand the legal data and connector ecosystem: Work closely with Business Development/Partnerships and Engineering to prioritize, integrate, and launch authoritative legal research sources (case law, citators, dockets, secondary sources) and system-of-record connectors across DMS, VDRs, CLM, e-discovery, and practice management (e.g., LexisNexis, Westlaw, iManage, NetDocuments, Datasite, Intralinks, Ironclad, Clio). - Build Legal Skills, Plugins, Teammates, and tailored onboarding: Design out-of-the-box legal workflows, domain-specific Skills, and tailored onboarding flows that ingest a lawyer’s or firm’s clause playbooks, precedent templates, and drafting conventions for immediate time-to-value. - Set the bar for accuracy, evaluations, and enterprise trust: Partner with AI Research and Engineering to build realistic, workflow-level legal benchmarks and evaluation harnesses (measuring citation fidelity, retrieval recall, tabular extraction, and redline quality), alongside enterprise controls for permissions, matter-level governance, and data handling. - Co-design with customers and accelerate vertical GTM: Build design partnerships with leading law firms and corporate legal teams, join strategic customer calls to turn live blockers into shipped product, and partner with Sales, Applied AI, and Product Marketing to craft category-defining demos, case studies, and self-serve and enterprise growth loops. QUALIFICATIONS - 1–4+ years of experience in product management, founding/early-stage product building, forward-deployed product/solutions, or a high-intensity analytical/operating role (such as startup operations, strategy consulting, or investment banking) paired with hands-on product shipping. We index heavily on slope, curiosity, and execution speed rather than years on a resume. - No JD or formal legal degree required—though genuine curiosity about how legal professionals research, analyze risk, negotiate, and deliver work is essential. - AI-native builder: You actively build with LLMs and agents. You are comfortable writing and tuning prompts and Skills, prototyping workflows end-to-end, reasoning about tool calls and context budgets, and designing evaluations and human-in-the-loop safeguards for non-deterministic systems. - Analytical and data-fluent: Comfortable writing SQL, pulling your own cohorts, instrumenting failure modes, running guarded experiments, and pairing warehouse metrics with qualitative user research to focus on what drives retention and repeat high-value usage. - Crisp communicator and high-velocity executor: Strong written and verbal communication; comfortable moving directly from a partner call with an Am Law firm into writing a tight spec with engineers and shipping iterations the same week. - High-ownership operator: Thrives in a small, agile, low-ego team where processes are still being defined and you own the full stack of the outcome—from multi-quarter vertical strategy down to dogfooding edge cases in redlined Word documents. NICE TO HAVE - Experience building or operating at a legal AI, legal tech, e-discovery, CLM, or vertical enterprise AI company (or working directly with law firms and corporate legal departments). - Familiarity with real-world legal workflows and tooling—such as litigation cite-checking (Shepard’s/KeyCite), M&A virtual data rooms, contract redlining playbooks, DMS/CLM integrations, or Microsoft Office add-ins. - Technical foundation (CS, engineering, data science, or dual technical/business training) with comfort reading API documentation, MCP/connector schemas, and system architectures.

Location: San Francisco; New York City In 2026, we launched Computer, the defining product for the new era of agentic AI. We’ve scaled beyond the millions of people using Perplexity every day for research, shopping, investing, and curiosity into a new paradigm of using AI to transform knowledge into action. Thousands of attorneys, Am Law firms, and corporate legal teams already rely on Perplexity every week—and Legal is one of our highest-conviction enterprise verticals. Following the playbook that scaled Perplexity Finance, we are looking for an entrepreneurial Product Manager to build and scale our Legal vertical from the ground up. Product Managers at Perplexity work closely with design, engineering, research, and go-to-market teams to turn frontier AI capabilities into indispensable daily workflows. Whether you have a couple of years of product experience at a legal AI or B2B software company, or you are an early-career builder or operator with high agency and a steep trajectory, this role offers rare end-to-end ownership of a flagship vertical. In your application, please highlight a product, workflow, or agent system you’ve built—or a specific legal problem you believe AI is uniquely positioned to solve. THE ROLE Legal work sits at the exact intersection where Perplexity shines: high-stakes research, multi-document synthesis, verifiable citations, and multi-step execution across specialized systems. Winning in Legal requires clearing an uncompromising bar for accuracy, source authority, document fidelity, and enterprise governance—without sacrificing the speed and simplicity that make Perplexity magical. Sitting within our AI Capabilities & Verticals PM team, you will be the dedicated product owner for Perplexity’s Legal vertical. Rather than building an isolated point solution, you will shape how core Perplexity surfaces—Computer, Search, Teammates, Projects, Plugins, Skills, and Artifacts—come together into a cohesive, trusted experience for litigators, transactional counsel, and in-house legal teams. You will partner across Engineering, Design, AI Research, Partnerships, Sales, and Product Marketing to close product and data gaps, co-design with leading law firms and legal departments, and scale Legal into one of Perplexity’s flagship enterprise businesses. WHAT YOU’LL DO - Own the Legal vertical roadmap end-to-end: Define and execute product strategy across litigation research, M&A and transactional diligence, contract review and drafting, and in-house legal workflows—translating attorney pain points into modular capabilities that benefit the entire platform. - Ship core legal primitives and entrypoints: Partner with Engineering and Design to build the product surfaces high-stakes legal work demands—including structured multi-document review tables for diligence and discovery, passage-level inline citations with side-by-side source verification across PDFs/DOCX/spreadsheets, precision redlining and document comparison, and seamless workflows inside Microsoft Word, Outlook/email, and Slack. - Expand the legal data and connector ecosystem: Work closely with Business Development/Partnerships and Engineering to prioritize, integrate, and launch authoritative legal research sources (case law, citators, dockets, secondary sources) and system-of-record connectors across DMS, VDRs, CLM, e-discovery, and practice management (e.g., LexisNexis, Westlaw, iManage, NetDocuments, Datasite, Intralinks, Ironclad, Clio). - Build Legal Skills, Plugins, Teammates, and tailored onboarding: Design out-of-the-box legal workflows, domain-specific Skills, and tailored onboarding flows that ingest a lawyer’s or firm’s clause playbooks, precedent templates, and drafting conventions for immediate time-to-value. - Set the bar for accuracy, evaluations, and enterprise trust: Partner with AI Research and Engineering to build realistic, workflow-level legal benchmarks and evaluation harnesses (measuring citation fidelity, retrieval recall, tabular extraction, and redline quality), alongside enterprise controls for permissions, matter-level governance, and data handling. - Co-design with customers and accelerate vertical GTM: Build design partnerships with leading law firms and corporate legal teams, join strategic customer calls to turn live blockers into shipped product, and partner with Sales, Applied AI, and Product Marketing to craft category-defining demos, case studies, and self-serve and enterprise growth loops. QUALIFICATIONS - 1–4+ years of experience in product management, founding/early-stage product building, forward-deployed product/solutions, or a high-intensity analytical/operating role (such as startup operations, strategy consulting, or investment banking) paired with hands-on product shipping. We index heavily on slope, curiosity, and execution speed rather than years on a resume. - No JD or formal legal degree required—though genuine curiosity about how legal professionals research, analyze risk, negotiate, and deliver work is essential. - AI-native builder: You actively build with LLMs and agents. You are comfortable writing and tuning prompts and Skills, prototyping workflows end-to-end, reasoning about tool calls and context budgets, and designing evaluations and human-in-the-loop safeguards for non-deterministic systems. - Analytical and data-fluent: Comfortable writing SQL, pulling your own cohorts, instrumenting failure modes, running guarded experiments, and pairing warehouse metrics with qualitative user research to focus on what drives retention and repeat high-value usage. - Crisp communicator and high-velocity executor: Strong written and verbal communication; comfortable moving directly from a partner call with an Am Law firm into writing a tight spec with engineers and shipping iterations the same week. - High-ownership operator: Thrives in a small, agile, low-ego team where processes are still being defined and you own the full stack of the outcome—from multi-quarter vertical strategy down to dogfooding edge cases in redlined Word documents. NICE TO HAVE - Experience building or operating at a legal AI, legal tech, e-discovery, CLM, or vertical enterprise AI company (or working directly with law firms and corporate legal departments). - Familiarity with real-world legal workflows and tooling—such as litigation cite-checking (Shepard’s/KeyCite), M&A virtual data rooms, contract redlining playbooks, DMS/CLM integrations, or Microsoft Office add-ins. - Technical foundation (CS, engineering, data science, or dual technical/business training) with comfort reading API documentation, MCP/connector schemas, and system architectures.