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Location: Washington, District of Columbia, United States Dexis is a dynamic professional services firm dedicated to partnering with government and community leaders both in the U.S. and internationally to achieve critical social outcomes in a rapidly changing world. At Dexis, you will experience a corporate culture of inclusiveness, respect, fairness, and trust. You will be given the means and mentorship needed to succeed, and your creativity will be rewarded. About the Position We are seeking a highly experienced Program Director/Team Lead to lead implementation of an anticipated Department of State program focused on monitoring and evaluation of rapid foreign assistance programs in dynamic and fragile contexts. The Program Director/Team Lead will oversee the operations and performance of the field team(s) and supporting staff. They will be responsible for overall contract performance, reporting, and client satisfaction. This position is based in the Washington, D.C. metropolitan area and is contingent upon award. Responsibilities Serve as Dexis' primary point of contact with the COR and Department of State stakeholders, overseeing overall contract implementation, execution, delivery, quality, and client satisfaction Oversee the operations and performance of field team(s), supporting staff, subcontractors, and implementing partners Lead identification and shaping of MEL and TPM support for humanitarian assistance activities Lead development of task order concepts and technical approaches from identification of opportunity through capture through to submission, negotiation and inception. Contribute to successful bids through developing technical approaches, building resources and workplans, and contributing to budget development Negotiate successful task order proposals to contract Coordinate task order capture efforts across technical and operational teams Provide strategic oversight across activities to ensure alignment with client priorities Manage on-the-ground operational and logistics requirements, including coordination across dispersed field teams, partners, and complex operating environments Coordinate with U.S. Government stakeholders, multilateral organizations, UN agencies, OCHA, UNHCR, WFP, NGOs, and other humanitarian coordination actors as needed Maintain awareness of global humanitarian crises and programmatic needs Represent Dexis in client engagements, briefings, coordination meetings, and field-facing partner discussions Serve as a deeply relational, externally facing leader who builds trust with clients, partners, field teams, and local stakeholders Monitor performance, risks, client feedback, and operational issues, and make strategic prioritization decisions in dynamic environments Minimum Qualifications Minimum 10 years of experience managing U.S. Government programs . Minimum five (5) years of experience serving as a Project Director, Program Director, Task Order Manager, Chief of Party, Team Lead, or in an equivalent senior project leadership role managing complex projects with multiple teams working simultaneously on different activities . Deep familiarity with delivery of U.S. federal humanitarian assistance, disaster response, stabilization, and/or similar crisis-oriented programming . Experience supporting humanitarian assistance or crisis response programs . Minimum five (5) years of experience managing MEL and/or TPM activities in complex environments . Experience managing on-the-ground operations and logistics, dispersed field teams, and coordination with local, international, and implementing partners . Bachelor’s degree required; Master’s preferred Preferred Qualifications Prior experience with USAID’s Bureau for Humanitarian Assistance (BHA), the Department of State’s Bureau for Population, Refugees, and Migration (PRM), the Department of State’s Bureau of Disaster and Humanitarian Response, and/or any of their predecessor offices, within the past three (3) years . Below is the pay range aligned with this position. When developing a range, Dexis evaluates compensation holistically, triangulating between external market research , our budget for the position, and internal equity to arrive at a figure that is fair and competitive. Offers within this range will be based on an individual candidate's qualification, relevant education and experience, skills, performance, and organizational needs. Dexis pay range for this role: $118,000 — $193,200 USD Benefits Dexis offers benefits to support employees’ health, financial security, and well-being. The benefits outlined below are for full-time, US-based positions only. These benefits include: Medical and prescription drug coverage: A choice of three UnitedHealthcare medical plans, with coverage options for employees and eligible dependents. Dental insurance: Dental coverage for employees and eligible dependents, including preventive, basic, major, and orthodontic services, subject to plan limits. Company-paid vision insurance: Vision coverage for employees and eligible dependents, with premiums paid in full by Dexis. Employer-funded health reimbursement arrangement (HRA): Employees who enroll in the Silver HRA medical plan receive an employer-funded HRA to help pay eligible in-network deductible expenses. Company-paid life and disability insurance: Basic life and accidental death and dismemberment (AD&D) insurance, plus short-term and long-term disability coverage. Optional supplemental insurance: Voluntary supplemental life and AD&D insurance options, including life insurance options for eligible dependents. Employee Assistance Program (EAP): Company-paid access to confidential counseling and legal and financial support resources for employees and their families. Health and wellness resources: Virtual care, behavioral health resources, and wellness programs available through the medical plan. Benefits assistance: Personalized support with benefit enrollment, coverage questions, claims, and finding providers through the Employee Care Center. Participation, coverage, and employee contributions are subject to applicable benefit plan terms and eligibility requirements. Dexis is on a mission to help solve today’s most pressing global political, social, and economic challenges and create a world where all people are safe and prosperous. As a Dexis employee, you will be challenged, empowered, and mentored. Our motto is “find a way or make a way” — that’s how Dexis goes “all in.” How will you? If you are passionate about this opportunity, apply now! Only those applicants who meet the above criteria will be contacted for interview. Dexis is an Equal Opportunity Employer, and does not discriminate on the basis of race, color, sex, national origin, religion, pregnancy, disability, age, genetic information, military service, veteran status, ethnicity, citizenship, sexual orientation, gender identity, marital status, childbirth and related medical conditions, including lactation, or any other protected class under applicable law.

Location: Munich Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW Harvey’s Legal Engineers are skilled lawyers from top-tier law firms who apply their legal experience to ensure that current and prospective customers understand how Harvey’s solutions enhance specific day-to-day workflows, working alongside Harvey’s Account Executives to support all aspects of our sales strategy. Legal Engineers build consultative relationships with law firm partners and associates and in-house attorneys at private equity firms and Fortune 500 companies, becoming trusted advisors on how Harvey’s AI solutions can make them more effective. Similar to how Solutions Architects secure the “technical win” in the sales process, Legal Engineers secure the “legal win” by performing in-depth customer discovery and education on Harvey’s solutions through targeted meetings and demos that resonate with the customer’s day-to-day workflows specific to their legal practice area. Legal Engineers utilize their experience practicing law and their legal mindset to ask thoughtful questions to understand the needs of law firm and in-house attorneys, develop credibility, and then partner with Account Executives to educate them on Harvey’s value via large and small group sessions as well as one-to-one conversations. WHAT YOU’LL DO - Engage with English- and German-speaking lawyers at existing and prospective customers to understand their workflow challenges, strategic objectives, and broader firm context — then demonstrate how Harvey’s AI solutions can address them. - Establish yourself as a credible expert in solving customers’ specific legal problems (e.g. researching public and private databases for certain types of information, drafting and analyzing contractual provisions and whole documents, analyzing briefs and filings, corporate governance, conducting due diligence). - Lead product demonstrations tailored to the context of various law firm practice groups and in-house legal teams, asking questions to validate how Harvey can add value and then showcasing Harvey’s features and benefits relevant to each prospective client’s potential use cases. - Partner with the marketing team to develop content that will resonate with lawyers, tailored to the unique needs of their practice areas and client types. - Act as the “Voice of the Customer,” using your legal perspective to help the broader sales team to develop and implement more effective strategies and synthesize customer feedback for the product team through a legal lens. - Tailor the introduction of new solutions to specific customer needs. - Further the market perception of Harvey as uniquely credible, substantive, and helpful in applying its AI solutions to make lawyers better at their jobs. - Conduct research and analysis on customers and competitors. WHAT YOU HAVE - JD or equivalent legal qualification. - Fluent in German and English. - At least 3 years of experience practicing law at a top-tier law firm (Vault 50 or equivalent), preferably with a transactional, in-house or transformation experience. - Executive engagement skills and presence, with an ability to establish strong relationships with key decision makers and build credibility at all levels. - Outstanding presentation skills to both legal and executive audiences, whether impromptu on a whiteboard or using presentations and demos. - Strong understanding of legal processes and challenges faced by legal professionals. - Curiosity about AI’s potential to transform the legal industry. - Sales or customer-facing experience, including law firm business development and/or secondment, is a plus, as is experience directly managing law firm client matters and client relationships. ADDITIONAL INFORMATION FOR POSTINGS - Location: Germany - Work eligibility: Must have valid German work rights; Harvey does not currently offer visa sponsorship for this role WHAT WE OFFER - Be part of building something special as a founding member of our Germany team - Opportunities to work on cross-functional go-to-market initiatives, with a focus on scaling sales strategy and driving revenue growth DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES [HERE https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922]. #LI-RC1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Montpellier, France Are you a health professional thinking about a career change? Are you passionate about how technology can help progress your profession? If you have an allied health background or previous experience as a Physical Therapist, a role as a Business Development Manager at VALD could be the change you need! About VALD VALD is the world leader in technology for the allied health industry, providing innovative human-measurement technology to over 8,000 clients in over 150 countries. If you have a favorite team in the NBA, EPL, or NFL, there's a good chance they use VALD Technologies. Since its humble beginnings in 2015 in Brisbane, Australia, VALD has grown to a team of over 300 team members in over 30 countries, with five offices across four continents. Driven by a multidisciplinary team of researchers, clinicians, sports scientists, designers, developers and engineers, VALD's suite of systems offer unparalleled insight into human movement, performance, injury risk and rehabilitation. About the VALD Business Development Team The Business Development team are on the front line for VALD. As part of a truly global team, you will attend conferences and perform product demonstrations (both in-person and teleconferences) in clinical, performance, and tactical settings. You'll set up and oversee product trials, nurture new leads and look for new opportunities for VALD. With an education-based approach to sales, as a Business Development Manager, you must have an intimate knowledge of VALD's systems. You'll leverage your industry expertise and product knowledge to demonstrate how our clients can get the most out of our systems to provide value to their business. Is this you? Prior experience working in a clinical or allied health setting, such as a physiotherapist/physical therapist or similar role. Excellent communication and interpersonal skills via various mediums, including team calls, in-person interaction and sales pipeline reporting. Be comfortable with targeting new clients. Willing and able to travel for client meetings and represent VALD at industry conferences and events. Confidence to persuasively demonstrate VALD systems and communicate product and industry knowledge to clients. A self-starter who holds themselves accountable for reaching sales targets. A desire to work with and nurture existing distributor relationships. Prior experience using CRMs and the Microsoft Office 365 suite of products. You reside in France. You speak French and English (please submit your application in English) It’s not expected that any single candidate would check every box here. If you meet just some of the requirements, but not all, we encourage you to submit your application! We strongly encourage you to apply if you’re at all interested. Show us how your experience could improve our team and widen our perspective. Our selection process includes assessing the requirements of the role vs the individual, and how well we think they will work in the VALD team. Why VALD? An opportunity to travel the world utilizing your health and performance experience is just the beginning when you join VALD.  Recently named in LinkedIn's Top 25 Startups for 2022 in Australia, VALD's best asset is not our technology but our people and culture. We have a range of benefits we offer to our team, such as: Industry-leading compensation with healthy performance-based incentives. The opportunity to work in a company that is redefining allied healthcare. Learn from a range of high-performing individuals and teams across various disciplines. Be part of a down-to-earth, inclusive and vibrant team. Regular travel opportunities to get the entire VALD team together for your ongoing development. The latest equipment and remote setup to perform at your best. VALD Diversity & Inclusion Commitment VALD’s best asset is not our technology but our people and culture. A culture of inclusion and diversity is critical to our business. We know diverse teams perform better. It's not a separate initiative – we aim to embed inclusion and diversity in everything we do. We are committed to fostering an inclusive work environment and embracing diversity, including gender, nationality, disability, age, marital/parental status, ethnicity, gender identity, socioeconomic background and sexual orientation. We welcome applications from people from all backgrounds. Conditions of Employment Successful applicants will be subject to background checks (including identity and criminal record checks). It will be a condition of employment that the background checks return acceptable results.

Location: Marseille, France Are you a health professional thinking about a career change? Are you passionate about how technology can help progress your profession? If you have an allied health background or previous experience as a Physical Therapist, a role as a Business Development Manager at VALD could be the change you need! About VALD VALD is the world leader in technology for the allied health industry, providing innovative human-measurement technology to over 8,000 clients in over 150 countries. If you have a favorite team in the NBA, EPL, or NFL, there's a good chance they use VALD Technologies. Since its humble beginnings in 2015 in Brisbane, Australia, VALD has grown to a team of over 300 team members in over 30 countries, with five offices across four continents. Driven by a multidisciplinary team of researchers, clinicians, sports scientists, designers, developers and engineers, VALD's suite of systems offer unparalleled insight into human movement, performance, injury risk and rehabilitation. About the VALD Business Development Team The Business Development team are on the front line for VALD. As part of a truly global team, you will attend conferences and perform product demonstrations (both in-person and teleconferences) in clinical, performance, and tactical settings. You'll set up and oversee product trials, nurture new leads and look for new opportunities for VALD. With an education-based approach to sales, as a Business Development Manager, you must have an intimate knowledge of VALD's systems. You'll leverage your industry expertise and product knowledge to demonstrate how our clients can get the most out of our systems to provide value to their business. Is this you? Prior experience working in a clinical or allied health setting, such as a physiotherapist/physical therapist or similar role. Excellent communication and interpersonal skills via various mediums, including team calls, in-person interaction and sales pipeline reporting. Be comfortable with targeting new clients. Willing and able to travel for client meetings and represent VALD at industry conferences and events. Confidence to persuasively demonstrate VALD systems and communicate product and industry knowledge to clients. A self-starter who holds themselves accountable for reaching sales targets. A desire to work with and nurture existing distributor relationships. Prior experience using CRMs and the Microsoft Office 365 suite of products. You reside in France. You speak French and English (please submit your application in English) It’s not expected that any single candidate would check every box here. If you meet just some of the requirements, but not all, we encourage you to submit your application! We strongly encourage you to apply if you’re at all interested. Show us how your experience could improve our team and widen our perspective. Our selection process includes assessing the requirements of the role vs the individual, and how well we think they will work in the VALD team. Why VALD? An opportunity to travel the world utilizing your health and performance experience is just the beginning when you join VALD.  Recently named in LinkedIn's Top 25 Startups for 2022 in Australia, VALD's best asset is not our technology but our people and culture. We have a range of benefits we offer to our team, such as: Industry-leading compensation with healthy performance-based incentives. The opportunity to work in a company that is redefining allied healthcare. Learn from a range of high-performing individuals and teams across various disciplines. Be part of a down-to-earth, inclusive and vibrant team. Regular travel opportunities to get the entire VALD team together for your ongoing development. The latest equipment and remote setup to perform at your best. VALD Diversity & Inclusion Commitment VALD’s best asset is not our technology but our people and culture. A culture of inclusion and diversity is critical to our business. We know diverse teams perform better. It's not a separate initiative – we aim to embed inclusion and diversity in everything we do. We are committed to fostering an inclusive work environment and embracing diversity, including gender, nationality, disability, age, marital/parental status, ethnicity, gender identity, socioeconomic background and sexual orientation. We welcome applications from people from all backgrounds. Conditions of Employment Successful applicants will be subject to background checks (including identity and criminal record checks). It will be a condition of employment that the background checks return acceptable results.

Location: New York, New York; New York City Metropolitan Area; New Jersey; Connecticut; San Francisco Bay Area, California Workplace: remote About the role: At Provectus, you don’t prototype in a sandbox and hand a client a slide deck. You embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production — then you watch the business number move. We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name What You’ll Do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice What We Look For: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses) Nice to have: Containers and orchestration (Kubernetes/ECS) and CI/CD in production IaC depth: AWS CDK, CloudFormation, Terraform Open-source contributions or public writing on applied AI What We Offer: Full-time employment On-site visits to clients’ facilities and our office in NYC 1/week Unlimited Vacation policy Generous health, vision, and dental insurance 401(K) matching plan Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data No Visa sponsorship How We Hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion. We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO

Location: Barcelona, Spain Workplace: remote Welcome to OLX  We're building marketplace sustainable ecosystems that millions of people depend on every month – to buy and sell cars, find homes, land jobs, and trade secondhand goods. It's commerce that matters: safe, smart, and environmentally responsible. We do this with courage to innovate, commitment to outcomes, collaboration across 50+ nationalities and 7 markets, and a customer-led approach that puts real people first. Add a desire to win – and you get a culture that's ambitious, fast-moving, and built on trust. Our brands – including AutoTrader, OLX, Otomoto, Property24, and more – are loved by millions. And we're backed by Prosus, one of the world's largest tech investors.  Join OLX and see how far you can go. We believe the future of our products sits at the intersection of AI and design. Our ambition is to become an AI-native organization, where intelligent systems and human-centered design come together to create faster, smarter, and more meaningful customer experiences. We’re rethinking how products are built, how experiences are shaped, and how teams deliver impact. A key part of this transformation is creating the right foundations and infrastructure to enable high-quality experiences at scale - where design systems, patterns, and workflows are structured, scalable, and AI-readable, unlocking new levels of speed, consistency, and innovation. The role We're looking for a Senior Product Designer to join our Design System team, working across our Real Estate products. You'll play a key role in evolving our design system, helping designers and engineers across the business design and build with greater consistency, quality and pace. You'll work day to day within a small, dedicated pod, spanning web and app. But the system serves designers across multiple tribes, each shipping their own product work. You'll work within our contribution model, helping teams outside the pod propose, adopt and evolve components without fragmenting the system. We're looking for someone with strong craft, attention to detail, and curiosity about systems thinking and AI-assisted workflows. You'll help create a coherent product experience across our brands while developing your own design systems practice. Key responsabilities: Design and evolve reusable components, patterns and foundations within our design system, reducing duplication and improving consistency across tribes Define component behaviour, states and variants, working directly with engineering to ship them Run and improve the contribution model: the process and standards that let designers outside the core pod propose and ship components without breaking system coherence Support design work from problem framing through to documentation and handover, using research and feedback from teams to inform decisions Create clear documentation and specifications covering variants, edge cases and usage guidance Collaborate closely with engineers on token strategy and the practical link between Figma and production code Resolve conflicts between a tribe's local need and the system's long-term coherence Work with product design teams to identify gaps and embed stronger systems thinking across products AI-enabled Design Systems: Use AI-assisted tooling as part of your daily workflow, from research through to prototyping and component definition Contribute to making the system well-structured for AI-assisted workflows, including tokens, documentation and reusable patterns Know when to override AI output with your own design judgment, and be able to explain why What we're looking for: Proven experience designing and maintaining a design system at scale, not just documenting one Experience running or contributing to a contribution model, or a clear point of view on how you'd build one Strong technical fluency: you understand how your decisions translate into code, and work with engineers as a peer, not a handoff Sharp judgment on trade-offs: when to enforce consistency, when to allow exceptions Strong communicator, able to justify design system decisions to stakeholders who don't share your priorities, and bring other designers along rather than dictate to them Comfortable with AI-assisted tools, with an interest in applying them in practical ways to improve speed, quality and consistency Required experience A portfolio demonstrating strong product and systems thinking, with evidence of shipped impact, not just documented patterns Experience working in Figma, including component libraries, variables and tokens, alongside experience with built or coded prototypes Experience working closely with engineers to deliver high-quality, scalable outcomes Experience or strong interest in AI-assisted design or development workflows Hiring Process First Stage - Recruiter Screen This is your first interview with our Talent Acquisition team. We’ll explore your background, skills, and experience, as well as your approach to autonomy, ownership, and critical thinking. It’s also a chance to discuss your aspirations and ensure alignment with our culture and values. Second Stage - Portfolio Review In this stage, you’ll meet with the Hiring Manager and a Designer from the team. We’ll explore your process thinking and approach to design through a case study of your choice. This is also a great opportunity to discuss how you collaborate with others and how your values align with our team culture. Third Stage  - AI Sandbox Challenge This is a dynamic and interactive session where you’ll have the chance to demonstrate your thought process in action. It’s designed to give us insight into how you approach challenges, integrate AI into your workflows, and apply your skills in a practical setting. We aim to make this process clear, collaborative, and reflective of the way we work as a team. DEI statement OLX values diversity and welcomes applicants of all races, ethnicities, disabilities, ages, genders, sexual orientations, religions, backgrounds, and experiences to apply. If this role excites you, we encourage you to apply, even if you don't meet all the requirements - you may be just the right fit for this or other opportunities with us.  Privacy Data disclaimer OLX will process your personal data to assess your fit for the applied position. You may optionally consent to store your data for up to 12 months after the application process for consideration in future OLX roles. For more details on how your application data will be processed please check our Privacy Statement.

Location: New York Workplace: remote About the role: We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name What You’ll Do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice What We Look For: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses) Nice to have: Containers and orchestration (Kubernetes/ECS) and CI/CD in production IaC depth: AWS CDK, CloudFormation, Terraform Open-source contributions or public writing on applied AI What We Offer: Full-time employment On-site visits to clients’ facilities and our office in NYC 1/week Unlimited Vacation policy Generous health, vision, and dental insurance 401(K) matching plan Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data No Visa sponsorship How we hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion. We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO

Location: United States; Phoenix; Seattle; California; Denver Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As an Account Executive at Cohere you will have ownership of the full sales cycle - from identifying leads to closing deals, with State, Local and Higher Education customers in the Western region of the United States. In this role you will be focussed on business development activity within the government departments and agencies at the state and local level, as well as within higher education within your territory.. We’re looking for an approachable and compelling communicator who loves working with SLED customers to uncover their needs and feels comfortable developing tailored value propositions around how Cohere’s platform can help them drive better citizen outcomes. You’ll lay the foundation for Cohere’s growth by owning your territory and collaborating with teammates across Customer Success, Sales Development, Marketing, and Sales Engineering. You’ll be the voice of the field and help our Product and Engineering teams prioritize the Cohere roadmap with customer-centric care. In this highly self-directed role, you will thrive in a quickly evolving environment. As an Account Executive, you will: - Drive net-new customer acquisition through targeted outbound activity, senior leader engagement, and relationship building across SLED organizations. - Develop and execute a sales plan and prioritization for the SLED market in your territory, identifying pathways and partners to scale growth regionally. - Act as a trusted advisor and thought partner to SLED customers and prospects by understanding their goals and shaping AI solutions that deliver measurable value - Work closely with channel and local partners, particularly Distributors and VARs as well as major system integrators to scale outreach, accelerate adoption, and maximize customer success - Leverage senior-level relationships with executives and government decision-makers to drive strategic opportunities and long-term partnerships - Collaborate with Product and Engineering teams on strategic efforts to deliver enterprise and public-sector solutions - Partner with SDRs and Marketing to drive top-of-funnel activity and overall territory growth - Own the full sales cycle; including discovery, technical and business validation, proof-of-concept, procurement, and deal close within a team-selling environment You may be a good fit if you have: - 5+ years of direct public sector sales experience in the SLED Market, with a proven track record of closing $2M+ annual quotas. - Deep knowledge of SLED procurement cycles and decision-making processes, how to work with resellers, VARs and distributors. - Established regional network, including state and local departments and agencies, prime contractors, and industry associations. - Experience selling SaaS, AI/ML, or enterprise software solutions to government clients. - High tolerance for ambiguity, you are both a strategist and a hands-on operator capable of building a market from the ground up - Strong organizational skills, with the ability to manage multiple internal and external stakeholders across fast-moving deals - Creativity and strong technical acumen to structure unique, mutually beneficial partnerships - Excellent communication skills, you listen deeply, understand what matters to senior decision-makers, and confidently present to both technical and non-technical audiences - Preference given to candidates within California, Texas, Washington, Arizona and Colorado with willingness to travel (25-35%). Cohere is committed to fair and transparent pay practices. The salary range listed for this role reflects the expected base compensation. Actual compensation offered will be determined by factors such as location, level, job-related knowledge, skills, education, and experience. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Technical Lead, Machine Learning to lead the execution of its AI platform by translating research into scalable, production-ready machine learning systems. This role sits at the intersection of research, infrastructure, and product, with responsibility for ensuring models are trainable, deployable, observable, and optimized for real-world performance. Working closely with research, engineering, and product teams, this position will drive the development of robust ML infrastructure while balancing performance, reliability, latency, and cost. Key Responsibilities Lead the end-to-end execution of machine learning systems, including data pipelines, training workflows, evaluation frameworks, inference architecture, and production deployment. Fine-tune and optimize models using modern techniques such as LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation . Design, build, and operate scalable inference systems with a focus on latency, cost efficiency, and reliability. Develop and maintain data pipelines for both synthetic and real-world training datasets. Build evaluation frameworks to measure model performance, robustness, safety, and bias in collaboration with research teams. Optimize production deployments through GPU utilization, memory efficiency, inference optimization, and scaling strategies. Partner closely with application engineering teams to integrate machine learning systems into backend, desktop, and mobile products. Continuously improve production systems through rapid iteration, monitoring, and data-driven optimization. Requirements Proven experience building and deploying production-grade machine learning systems used by real users. Strong expertise working with large language models and understanding model behavior, limitations, and failure modes. Experience developing scalable ML infrastructure, training pipelines, and inference systems. Strong software engineering skills with the ability to write maintainable, production-quality code. Experience balancing real-world production constraints, including latency, reliability, scalability, cost, and safety. Strong ownership mindset with the ability to independently drive technical initiatives from design through deployment. Excellent communication and collaboration skills, with experience working in cross-functional, high-performing engineering teams. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based model training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Senior Machine Learning Engineer to design and build production-grade machine learning systems that power its AI platform. This is a hands-on technical role focused on solving complex machine learning challenges, translating research into scalable solutions, and delivering reliable AI systems that operate effectively in real-world environments. Working closely with research, product, and engineering teams, this position will independently own critical machine learning components from development through production deployment. Key Responsibilities Build and develop core machine learning systems that power AI-driven product capabilities. Own the end-to-end machine learning lifecycle, including data preparation, model training, evaluation, inference, deployment, and continuous iteration. Translate research concepts into reliable, production-ready machine learning solutions. Investigate and resolve model performance issues and production system failures using real-world operational insights. Continuously improve machine learning systems through rapid experimentation, measurement, and iteration. Collaborate closely with research, product, and engineering teams to deliver impactful AI features. Provide technical guidance through code reviews, best practices, and mentorship of fellow machine learning engineers. Develop solutions that balance real-world production requirements, including latency, scalability, cost efficiency, reliability, and safety. Requirements Proven experience building and deploying production machine learning systems used by real users. Strong understanding of modern machine learning models, including their behavior, limitations, and failure modes in production environments. Excellent software engineering skills with the ability to develop robust, maintainable, production-quality systems. Experience designing and implementing scalable machine learning pipelines and infrastructure. Strong ownership mindset with the ability to independently solve complex technical challenges from concept through deployment. Excellent problem-solving, communication, and collaboration skills within cross-functional engineering teams. Demonstrated ability to iterate quickly and continuously improve machine learning systems based on production feedback. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Principal Machine Learning Engineer to build and deploy production-grade machine learning systems that power its AI platform. This role focuses on translating research into scalable solutions by developing robust training pipelines, inference systems, evaluation frameworks, and deployment infrastructure. Working closely with research and application engineering teams, this position will play a key role in delivering reliable, high-performance ML systems that operate effectively under real-world production constraints. Key Responsibilities Build and own end-to-end machine learning pipelines covering data processing, model training, evaluation, inference, and deployment. Fine-tune and adapt models using modern techniques such as LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation. Design and operate scalable inference systems while balancing latency, cost, and reliability. Develop and maintain data pipelines for both synthetic and real-world training datasets. Build evaluation frameworks to assess model performance, robustness, safety, and bias in collaboration with research teams. Optimize production deployments through GPU optimization, memory efficiency, latency reduction, and scaling strategies. Collaborate with application engineering teams to integrate machine learning systems into backend, mobile, and desktop applications. Continuously improve ML systems through rapid iteration and real-world performance monitoring while balancing production constraints such as latency, cost, reliability, and safety. Requirements Strong background in deep learning and transformer-based architectures. Hands-on experience training, fine-tuning, or deploying large-scale machine learning models in production. Proficiency with modern machine learning frameworks such as PyTorch or JAX . Experience with distributed training and inference frameworks, including technologies such as DeepSpeed, FSDP, Megatron, ZeRO, or Ray . Strong software engineering skills with experience building robust, maintainable, production-grade systems. Experience optimizing GPU workloads, including memory efficiency, quantization, and mixed precision. Ability to independently own end-to-end machine learning systems in fast-moving environments. Strong problem-solving skills with a focus on rapid iteration and continuous improvement. Preferred Qualifications Experience with one or more of the following is preferred: LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer Open-source contributions to machine learning or systems libraries Scientific computing, compiler technologies, or GPU kernel development Reinforcement Learning from Human Feedback (RLHF) pipelines, including PPO, DPO, or ORPO Training or deploying multimodal or diffusion models Large-scale data processing frameworks such as Apache Arrow, Spark, or Ray

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking an iOS Software Engineer to build and enhance its AI-native mobile experience. This role is responsible for developing production-grade iOS applications where AI interactions are central to the user experience, ensuring performance, reliability, and user trust across all mobile interactions. Working closely with backend and machine learning teams, this position will focus on delivering scalable iOS applications that integrate advanced AI capabilities while maintaining a seamless and intuitive user experience. Key Responsibilities Build and maintain production iOS applications using Swift and SwiftUI . Integrate AI-powered features through backend APIs. Design user experiences for AI interactions, including loading states, streaming responses, retries, and fallback mechanisms. Optimize application performance, memory usage, and battery efficiency. Implement user feedback and analytics mechanisms to support AI evaluation and continuous product improvement. Collaborate closely with backend and machine learning engineers on API design and system behavior. Maintain high standards of application quality, stability, and reliability for App Store releases. Requirements Minimum 3 years of iOS development experience using Swift. Hands-on experience integrating AI-powered features into mobile applications. Strong understanding of async/await , concurrency, and background task management. Solid experience optimizing iOS application performance, memory usage, and responsiveness. Experience developing, releasing, and maintaining production iOS applications. Familiarity with designing applications that operate reliably under latency, partial failures, and non-deterministic AI behavior. Exposure to CoreML or lightweight on-device machine learning is an advantage. Familiarity with feature flags or remote configuration systems is preferred. Strong understanding of user experience design for AI-powered applications, with an emphasis on usability and user trust. Preferred Technical Skills Experience with the following technologies is preferred: Swift SwiftUI Swift Package Manager (SPM) SQL and NoSQL databases TensorFlow Lite (on-device inference)

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is looking for a Full Stack Engineer – AI Systems to build AI-native product experiences that transform advanced AI capabilities into intuitive, production-ready workflows. This role combines frontend, backend, and AI engineering to develop intelligent features that are reliable, scalable, and user-centric. Working closely with product, backend, and machine learning teams, this position will focus on designing end-to-end AI workflows, integrating large language models (LLMs), and delivering seamless user experiences across web applications. Key Responsibilities Build end-to-end product features across frontend, backend, and AI integrations. Design and develop AI agent workflows that support planning, tool usage, failure handling, and recovery across multiple steps. Integrate LLMs, memory systems, and external tools into scalable, production-grade applications. Design responsive AI interactions with streaming capabilities, partial results, and low-latency performance. Improve system reliability, observability, and fallback mechanisms for AI-powered features. Collaborate closely with product, backend, and machine learning teams to deliver features from concept to production. Continuously iterate and improve product functionality based on user feedback, production insights, and real-world usage. Requirements Strong experience in full stack software engineering across frontend and backend development. Solid understanding of system design, scalable architecture, and API development. Experience building AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or similar technologies. Ability to work effectively in fast-paced environments with evolving requirements. Strong ownership mindset with experience delivering features from ideation through production deployment. Excellent problem-solving skills and the ability to make pragmatic engineering decisions in ambiguous situations. Preferred Technical Skills Experience with some or all of the following technologies is preferred: Next.js Python Node.js PyTorch OpenAI, Anthropic, or open-source Large Language Models (LLMs) SQL and NoSQL databases Kubernetes Docker

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking an Android Software Engineer to build and enhance its AI-native mobile experience. This role is responsible for developing production-grade Android applications where AI is at the core of the user experience, ensuring performance, reliability, and usability across all mobile interactions. Working closely with backend and machine learning teams, this position will focus on delivering scalable Android applications that integrate advanced AI capabilities while maintaining a seamless user experience. Key Responsibilities Build and maintain production Android applications using Kotlin . Integrate AI-powered features such as chat, vision, voice, and recommendation systems through backend APIs. Design intuitive user experiences for AI interactions, including streaming responses, retries, and partial results. Optimize application performance, memory usage, and responsiveness for AI-intensive workflows. Implement analytics, logging, and user feedback mechanisms to support continuous AI evaluation and product improvement. Collaborate closely with backend and machine learning engineers to define API integrations and system behavior. Ensure application stability, security, and scalability within production environments. Requirements Minimum 3 years of Android application development experience using Kotlin. Hands-on experience integrating AI-powered features, such as Large Language Models (LLMs), computer vision, or speech APIs. Strong understanding of asynchronous programming using Coroutines and Flow . Experience working with RESTful or gRPC APIs and structured data formats. Strong debugging, troubleshooting, and performance profiling skills. Experience developing applications that operate reliably under conditions involving latency, partial failures, and non-deterministic behavior. Familiarity with ML Kit or lightweight on-device inference is an advantage. Experience publishing and maintaining production applications on the Google Play Store . Preferred Technical Skills Experience with the following technologies is preferred: Kotlin / Java SQL and NoSQL databases TensorFlow Lite (on-device inference)

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a AI Backend Engineer to build and operate the backend infrastructure that powers AI-driven experiences across its products. The role focuses on owning the inference and orchestration layer that sits between AI models and end users, ensuring every interaction is fast, reliable, scalable, and cost-efficient. Working closely with engineering and AI teams, this position will play a key role in designing production-grade backend services, optimizing system performance, and delivering robust AI-powered features across mobile and desktop platforms. Key Responsibilities Build, maintain, and operate backend systems that power AI-enabled features in production. Design and implement AI inference pipelines, orchestration layers, and service architectures around AI models. Develop scalable, high-performance APIs that integrate seamlessly with frontend applications and machine learning systems. Optimize system performance by improving inference latency, throughput, caching, batching, and streaming capabilities. Own production operations, including monitoring, logging, alerting, and incident response. Troubleshoot and resolve issues within distributed systems to ensure service reliability and stability. Continuously improve backend architecture and production systems based on operational insights and real-world usage. Collaborate with cross-functional teams to deliver reliable, scalable, and high-quality AI-powered solutions. Requirements Strong backend engineering experience in production environments. Proven experience building and operating high-throughput, low-latency backend services. Experience designing scalable APIs and distributed systems. Familiarity with AI inference patterns, including Large Language Models (LLMs), embeddings, and multimodal AI systems. Strong debugging and troubleshooting skills within distributed production environments. Demonstrated ability to deliver production-ready solutions while iterating based on real-world system performance. Excellent analytical, problem-solving, and collaboration skills. Technical Skills Experience with the following technologies is preferred: Python Node.js PyTorch OpenAI, Anthropic, or open-source Large Language Models (LLMs) SQL and NoSQL databases Kubernetes Docker

Location: San Francisco, CA | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We are seeking a Director, Technical Accounting – M&A to join our Finance team at Anthropic. In this role, you will support the company's accounting for mergers, acquisitions, strategic investments, and other complex capital transactions. You will report to the Senior Director, Technical Accounting – M&A As Anthropic continues to scale rapidly and deploy capital into acquisitions, strategic investments, joint ventures, and novel commercial structures, you will be a key technical resource on structuring alternatives, consolidation outcomes, and financial statement impact. You will partner closely with Corporate Development, Legal, Tax, Treasury, FP&A, and leadership to ensure that deal economics are accurately reflected under US GAAP and that positions are defensible to external auditors, valuation specialists, and future regulators. This is a builder role: you'll help operate and continuously sharpen the controls, valuation governance, and close-ready documentation expected of a large accelerated filer, working alongside the Senior Director as the function takes shape. If you thrive on being in the room when deals are shaped — and then making the accounting land cleanly — we want to hear from you. In this role, you will: Execute technical accounting for business combinations, asset acquisitions, joint ventures, and related financing/equity structures Partner with and influence Corporate Dev to steer deal structures toward preferred terms and outcomes Perform accounting due diligence on prospective transactions, advising Corporate Development and leadership on GAAP, control, and earnings implications before terms are finalized Execute end-to-end purchase accounting — acquirer and acquisition-date identification, consideration measurement (contingent consideration, rollover equity, replacement awards), and recognition/measurement of assets, liabilities, and goodwill Execute post-close integration accounting — conforming accounting policies, system/ledger onboarding, working capital true-ups, earn-out remeasurement, and push-down considerations Assess and monitor consolidation and investment classification for investees and structured arrangements — VIE/primary-beneficiary analysis, reconsideration events, equity method, measurement alternative, and fair value through earnings — and support impairment and observable-price-change reviews Manage third-party valuation specialists; review PPA, intangible asset valuations, contingent consideration fair values, and impairment analyses Author and defend technical accounting policies & memoranda; partner closely with external auditors on M&A, investment, and consolidation matters Partner with Tax on deal structuring and ASC 740/basis-difference impacts; with Treasury and Legal on equity, SAFE/convertible, and other financing instruments Help refine the deal-accounting operating model — diligence checklists, Day-1 close playbooks, opening balance sheet procedures, measurement-period tracking, integration workplans, and SOX-ready controls over non-routine transactions Prepare and review transaction-related disclosures for quarterly and annual filings, including pro forma financial information and significance testing Present transaction accounting conclusions and financial statement impacts to leadership and cross-functional stakeholders in clear, decision-ready terms Monitor standard-setting and SEC developments affecting business combinations, consolidation, and investments; support adoption and cross-functional education You may be a good fit if you: Have 10+ years of progressive accounting experience, including 4+ years owning complex M&A and strategic investment accounting transactions end-to-end Hold an active CPA license Bring significant Big 4 experience — ideally in a National Office, Transaction/Deal Advisory, or Capital Markets/Accounting Advisory group — paired with in-house experience at a high-growth or public technology company Have contributed to multiple closed acquisitions and minority/strategic investments, including at least one transaction of meaningful scale or complexity Possess deep command of US GAAP for business combinations, consolidation, equity method, and fair value measurement, with a track record of positions that withstand auditor and regulator scrutiny Are fluent in valuation concepts and can direct and challenge third-party specialists on PPA, contingent consideration, and impairment models Have operated within a deal-accounting or investments-accounting function, contributing to playbook and controls design Communicate effectively with Corporate Development and Legal on structuring trade-offs, translating technical conclusions for cross-functional and senior stakeholders Demonstrate exceptional written and verbal communication, translating complex deal accounting into clear business implications Excel at hands-on technical execution in a fast-paced, ambiguous environment, partnering closely with the Senior Director on strategic judgment calls Are proficient with accounting systems (Workday preferred), consolidation tools, and advanced Excel/modeling Curious about and quick to adopt new AI tools, including Claude and Claude for Finance Strong candidates may also: Have deep, practitioner-level expertise in one or more of the following: Business combinations and asset acquisitions (ASC 805), including contingent consideration, replacement share-based awards, and step acquisitions Consolidation and investment classification (ASC 810, 323, 321), including VIE/primary-beneficiary analysis, basis differences, and the measurement alternative Fair value measurement, acquired financial instruments, and goodwill/intangibles (ASC 820, 815, 825, 350, 360), including impairment testing and IPR&D Have led accounting for carve-outs, divestitures, spin-offs, or legal-entity rationalizations, including standing up SOX-compliant controls over non-routine/complex transactions Have prepared or reviewed pro forma financial information and registration-statement disclosures (Article 11 of Regulation S-X, S-X Rule 3-05/1-02(w) significance testing, S-1 processes) Have experience with novel AI/technology deal structures — acqui-hires, IP/license-heavy transactions, data and compute arrangements, revenue-share partnerships, and strategic investor rights — and are passionate about leveraging AI to accelerate diligence, memo drafting, and close Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $230,000 — $300,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Code RL at Anthropic drives reinforcement learning efforts behind Claude's coding capabilities, creating and scaling agentic coding environments. This is an engineering role with unusual latitude to set technical direction and standards. You'll be part of a team solving the engineering side of research efforts such as embedding with research teams, getting up to speed on their systems and needs, and designing the frameworks, APIs, and infrastructure that let researchers move faster, then rotating off, leaving behind well-oiled systems those teams can understand, own, and maintain themselves. Your remit also includes the ongoing health of production RL runs: maintainable, monitored, and straightforward to triage. The team's problem space spans the client side of sandboxed execution for agentic RL environments, large-scale data processing jobs, the lifecycle of production datasets, and the frameworks researchers build environments on. You won't own all of this yourself, you'll take on the slices where your depth matters most. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and hard-won intuition for how complex systems fail — especially silently. You should be comfortable diving into messy research code, finding the load-bearing abstractions, and improving them incrementally while researchers continue to build on top of your work. Key responsibilities Design widely-used APIs, frameworks, and abstractions that other engineers and researchers build on, with careful attention to interface legibility and principled defaults Embed with research teams on a rotational basis: understand their engineering needs, build systems and APIs that support their work, and transfer ownership so teams can maintain those systems after you rotate off Work directly in research codebases, improving reliability and structure without slowing down the research they support Anticipate silent failure modes and prevent them structurally through type safety, well-designed invariants, targeted testing, and refactors that shrink the surface area for bugs Contribute to the reliability of production RL systems, including monitoring, regression detection, and triage tooling Help define engineering standards, review practices, and design patterns for a new team, and mentor researchers and engineers in adopting them Minimum qualifications Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant Python code A track record of designing intuitive, safe APIs or frameworks that other engineers or teams adopted and built on Experience working productively in large, evolving, or research-style codebases that you didn't originally write Demonstrated ability to anticipate failure modes — especially silent ones — and prevent them structurally through system design, type safety, and testing Strong written and verbal communication skills, including the ability to explain system designs to collaborators with varied engineering backgrounds Comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome Preferred qualifications Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows Familiarity with reinforcement learning concepts, agentic systems, or LLM training pipelines Experience building or operating large-scale distributed systems Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms Experience with large-scale data processing or dataset lifecycle management Experience designing plugin systems or extensible class hierarchies used across an organization Experience embedding with or consulting for other teams, including successfully handing off systems for others to own Experience defining code standards, lint rules, or static verification approaches adopted across multiple teams Prior experience as a technical lead, or setting engineering standards for a team Prior experience maintaining an open source project Representative projects These are examples of the challenges the team tackles; no one person will work on all of them: Design a base RL environment abstraction general enough to be subclassed across a wide range of environments Design a model-tool interface for sandboxed agentic environments that has explicit serialization semantics Partner with the platform teams that own the sandbox runtime to specify low-level features that improve the integrity of agentic coding tasks Design probes that catch sandbox regressions early Design the lifecycle and maintenance scheme for a production dataset Lead a research code refactor replacing loosely structured data containers with equivalents that carry stronger correctness guarantees, without breaking the experiments that depend on them Design lint rules and code-style requirements that favor statically verifiable patterns — including patterns less likely to be overlooked by an LLM reviewing or writing the code — to shrink the surface area for silent bugs Build the access layer that lets researchers discover and reuse data artifacts across teams The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $625,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Environments organization builds and maintains the infrastructure that improves Claude’s capabilities through reinforcement learning. That includes the frameworks researchers use to build environments and the infrastructure responsible for running them. The team's mission is to productionize research. You'll embed with research teams, get up to speed on how they work, and design the frameworks and APIs that let them move faster, building systems the team can understand, own, and maintain themselves. Scope also includes keeping production RL runs healthy, maintainable, monitored, and easy to triage. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and good intuition for how complex systems fail, especially silently. It's a bonus if you've built and operated a stateful distributed system, such as a workflow engine, actor framework, or durable-execution runtime, where correctness depends on getting shared state and recovery right. You should be comfortable diving into messy research code, finding the abstractions that matter, and improving them incrementally while researchers continue to build on your work. You should also be comfortable using AI tools to accelerate your own development, but have an impulse towards deep verification. Key responsibilities Design widely used APIs, frameworks, and abstractions that other engineers and researchers build on, making correct usage the default and ruling out entire classes of errors structurally Own the platform layers that sit beneath every environment, including the agent runtime Build the tooling that lets environment owners understand, debug, and maintain their environments in production without needing an infrastructure engineer in the loop Embed with research teams on a rotational basis, work directly in their codebases without slowing down the research they support, and transfer ownership when you rotate off Anticipate silent failure modes and prevent them structurally through type safety, well-designed invariants, targeted testing, and refactors that reduce the room for correctness issues Drive adoption of new frameworks across the organization, including deprecations and cutovers Help define the engineering standards, review practices, and design patterns for a new team, and mentor researchers and engineers in adopting them Minimum qualifications Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant code Strong taste in API and framework design, the ability to explain why an interface is right or wrong rather than just recognizing it, and a track record of other engineers or teams adopting and building on frameworks you have built Experience designing or operating stateful concurrent or distributed systems, and reasoning carefully about failure, retries, idempotency, and consistency A habit of verification: you measure before you conclude, and you build the checks that let a system show it's correct Experience working productively in large, evolving, or research-style codebases that you didn't originally write Strong written and verbal communication with collaborators of varied engineering backgrounds, and comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome Preferred qualifications Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows, and familiarity with agentic systems or LLM training pipelines Experience building agent frameworks, orchestration engines, or multi-agent systems, including checkpoint and restore, replay, and coordination of long-running stateful processes Experience using AI coding tools on code where correctness matters, with good judgment about what to delegate and how to make the results verifiable Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms Experience with large-scale data processing, dataset lifecycle management, or data lineage systems Experience designing serialization schemes, plugin systems, or extensible class hierarchies used across an organization Experience embedding with or consulting for other teams and handing off systems for others to own, or defining code standards adopted across teams, or prior experience as a technical lead Representative projects These are examples of the challenges the team tackles: Design a base RL environment abstraction that can be subclassed to support the large majority of environments built across RL Redesign the model-tool interface for sandboxed agentic environments so that state is guaranteed to survive serialization, making it structurally impossible to write a tool that silently loses state Design the state-sharing and recovery model for multi-agent workloads, so that losing a sandbox partway through a task becomes a transparent resume rather than lost work Define the failure and retry model for a sandboxed execution platform, distinguishing infrastructure faults from genuine task outcomes so that each is handled correctly Build the tooling that lets an environment owner diagnose why their environment is unhealthy in a production run, and fix it themselves The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $605,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.