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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 As the VC Partnerships Lead at Anthropic, you will drive transformative growth and strategic alignment by forging and managing high-impact startup partnerships. You will drive the adoption of Anthropic's cutting-edge AI capabilities within the startup ecosystem. In this role, you will design and execute innovative programs that enable startups to easily access and utilize Anthropic's advanced AI models. Your goal will be to scale our reach and impact by engaging with startups directly and through the accelerator ecosystem. This is an individual contributor role with broad ownership — you'll operate with high autonomy, partnering closely with sales, marketing, and product teams to build and run our startup partnerships motion. Key responsibilities Develop and lead Anthropic's startup partnerships strategy, leveraging our AI technology and industry partnerships Build relationships with key VC firms, and entrepreneurial communities Create compelling startup-focused offerings, programs, and growth initiatives Cultivate strong relationships with current and new accelerator partnerships; build out relationship models, own touch points, and drive outcomes such that accelerator portfolio companies are choosing to build on Claude Plan and execute startup-focused events, campaigns, and promotions to drive awareness and adoption Gather product feedback and represent the needs of the startup community to inform Anthropic's product roadmap Track and report on key metrics to measure the success and ROI of startup initiatives Minimum qualifications Have 7+ years of experience in partnerships, founder/operator roles, growth, or technical GTM roles—we're looking for builders Have a deep understanding of the startup ecosystem and AI/ML technology landscape—can speak credibly about technical products to technical audiences Have built relationships with VCs, worked at a VC firm, or successfully partnered with accelerators to drive portfolio engagement Excel at 0-to-1 program building—comfortable building from scratch, wearing multiple hats, and scaling based on data Proven ability to develop and execute complex, cross-functional go-to-market programs Possess exceptional communication skills—outstanding writer who crafts narratives for founders, developers, and VCs Thrive in fast-paced environments with bias to action and comfort with ambiguity BA/BS degree or equivalent practical experience Preferred qualifications Founded a company or led product at a high-growth startup Direct experience working for or with venture capital firms like Y Combinator, Lightspeed Ventures, Accel, a16z, Sequoia Capital Technical background—former developer, PM with hands-on coding experience, or deep familiarity with AI/ML development workflows Developer advocate or developer relations background with active presence in technical communities Familiarity with large language models and their applications in generative AI Existing relationships with venture capital firms, startup accelerators, and entrepreneurial communities 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: $215,000 — $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 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 As Data Operations Manager, you'll build and scale data operations across research teams working on frontier AI capabilities. You'll partner with researchers to design and execute data strategies, manage vendor relationships, and own the entire data pipeline from requirements to production. This role requires operational excellence combined with technical depth to understand what makes high-quality training data, but your focus will be on strategy and execution. About the Impact The data operations you build will directly determine how well our models perform on critical capabilities—tool use accuracy, prompt injection robustness, long-horizon reasoning, and safety alignment. You'll work with world-class researchers advancing the frontier while building the operational infrastructure to scale these efforts. We're looking for someone who gets excited about the challenge of scaling quality across diverse research areas—someone who can understand nuanced technical requirements, build the right partnerships, and execute flawlessly. If you thrive at the intersection of operational excellence and cutting-edge AI research, we'd love to hear from you. Responsibilities: Own and execute data strategy for research teams advancing frontier AI capabilities across RLHF, safety, tool use, and agentic workflows Drive strategic vendor partnerships and build scalable frameworks for technical data collection at scale Design and implement operational systems that translate research requirements into high-quality data pipelines Build evaluation frameworks and quality standards that ensure data meets the bar for training state-of-the-art AI systems Lead cross-functional initiatives to optimize research velocity while maintaining rigorous quality standards Proactively identify risks, bottlenecks, and opportunities to improve efficiency and effectiveness across data operations Partner with senior research leaders to align data operations with model development roadmaps and strategic priorities You may be a good fit if you: Have 3+ years in operations, consulting, product management, or program management roles Have exceptional project management skills with ability to handle multiple complex projects simultaneously Have strong communication skills and can engage effectively with technical and non-technical stakeholders Are familiar with how LLMs work or have strong interest in understanding AI training methodologies Are highly organized and can navigate ambiguity effectively Have experience with data analysis tools (SQL, Python, Tableau, spreadsheets, or similar) Thrive in fast-paced research environments with shifting priorities Are passionate about AI safety and understand the critical importance of high-quality data Strong candidates may also have: Experience with data collection, labeling, or annotation operations for AI/ML systems Knowledge of RLHF, constitutional AI, or human-in-the-loop workflows Background working with research teams at AI companies or research-oriented organizations Experience managing vendor relationships or external contractors Consulting background with experience translating complex requirements into deliverables Track record of implementing process improvements or quality control systems at scale 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: $270,000 — $365,000 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 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. We're seeking an exceptional Research Scientist to join our Life Sciences team at Anthropic. Our team is building a world-class research group focused on making Claude a superhuman life sciences research assistant. This role sits at the intersection of machine learning, software engineering, and biology — you'll directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development. As a core member of our Life Sciences team, you'll work in a high-impact team that translates deep biological domain knowledge into model training objectives, benchmarks, and agentic workflows. You'll help establish Anthropic as a leader in AI-accelerated biology while shaping how frontier models reason about and execute computational biology tasks. This role offers a unique opportunity to shape how frontier AI models learn to do biology. You'll work alongside some of the world's best AI researchers while tackling problems that matter for human health and scientific understanding. If you're excited about turning your computational biology expertise into model capabilities, we want to hear from you. Key Responsibilities Build and ship agentic tools and integrations that let Claude execute real life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review Design and build evaluation benchmarks that measure model capabilities on biology tasks — figure interpretation, bioinformatics, protocol reasoning, literature synthesis Work closely with product and design teams to scope, prototype, and ship features for life sciences users Partner with external biotech, pharma, and academic users to understand their workflows and turn feedback into product improvements Build and maintain the engineering infrastructure behind our biology product surface — tool scaffolding, data pipelines, eval harnesses Translate biological domain knowledge into product requirements and evaluation criteria that guide model improvement Minimum Qualifications Experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Experience working in drug discovery or development at a biotech or pharma company, or conducted fundamental research in an academic setting — with an understanding of what real scientific workflows look like and where they break down Strong software engineering skills: comfortable building production-quality Python, working in large codebases, and owning infrastructure end-to-end Hands-on experience training or fine-tuning ML models (LLMs, protein language models, or other deep learning architectures) A track record of shipping computational tools or pipelines that biologists actually use Comfortable navigating ambiguity and defining problems in a rapidly evolving research environment Able to work independently while collaborating tightly with research, product, and domain-expert teams Results-oriented with a bias toward rapid iteration and measurable impact Passionate about using AI to accelerate scientific discovery while maintaining high ethical standards Preferred Qualifications 5+ years of experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Ph.D. in computational biology, bioinformatics, bioengineering, CS, or a related quantitative field — or equivalent industry experience Experience with LLM post-training: RLHF, RL from verifiable rewards, SFT data curation, or eval-driven development Direct experience with therapeutic discovery pipelines — target identification, lead optimization, ADMET modeling, or clinical data analysis Familiarity with bioinformatics tooling and pipelines (sequence analysis, structure prediction, single-cell, variant calling, etc.) Experience building agentic systems or tool-use environments Published research in ML for biology, or open-source contributions to computational biology tools Fluency with biological databases (UniProt, PDB, Ensembl, NCBI) and the ability to reason about their schemas and failure modes 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: $300,000 — $320,000 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 The Computer Use team teaches Claude to see and operate computer interfaces, and builds the agent harness and end-user products that turn that capability into real tools. The team sits inside Anthropic's research organization and closes the loop between product and model. As a Product Engineer on this team, you'll own end-to-end delivery of our computer-use and browser-control product surfaces. You'll build across the full stack, from the user interface to the agent runtime to the backend services behind it. You'll work directly alongside researchers, with no layers between you and the model or the user. This is a dynamic role in which priorities evolve frequently. Success depends on a high tolerance for ambiguity, the adaptability to shift focus as needs change, and the agility and discernment to continuously prioritize the highest impact work. Key responsibilities Own end-to-end delivery of computer-use and browser-control product surfaces: scope, build, ship, measure, and iterate Diagnose and resolve reliability and robustness issues in the computer-use agent harness that block real-world usage Partner with computer-use researchers Partner with the Claude Cowork team on shared surfaces, integrations, and knowledge-worker workflows Instrument products and use usage data to drive prioritization and measure progress Translate fuzzy user pain points into concrete, shippable features for knowledge workers Minimum qualifications Experience building and shipping a product from zero to one with end-to-end ownership, as a founding or early engineer at a startup or with equivalent ownership inside a larger company Strong full-stack engineering skills, including production web frontend and backend development Hands-on experience building with LLM APIs, prompting, or agent frameworks A track record of shipping to external users and iterating based on their feedback Preferred qualifications Strong product design instincts and the ability to produce a clean, usable interface without a dedicated designer Experience with browser automation, desktop automation, or robotic process automation systems Experience building evals or quality harnesses for machine learning systems Comfort with lightweight data analysis, such as SQL, notebooks, and defining and tracking product metrics Experience designing agent loops, tool integrations, or guardrails for LLM-based systems Representative projects Own and resolve the top reliability and robustness issues on the computer-control and browser-control product surfaces, with measurable improvement in task success rate Take a net-new computer-use powered workflow from concept to external users, including instrumentation and a readout on usage 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: $300,000 — $320,000 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 customers renew on a mix of committed and consumption contracts, and the number of renewals is growing faster than any team of people could keep pace with. We don't want to answer that by hiring hundreds of renewal managers. We want renewals to run as a system: Claude and agents do most of the work, from spotting risk to drafting the offer to closing a standard renewal in product, and people step in where judgment, negotiation or relationships matter. You'll design, build and run that system. You'll own the renewal outcome for the business globally and the product and technology that delivers it. You'll lead a small team of builders and the human layer, internal specialists and outsourced partners, that handles what agents can't yet. You'll work closely with Sales, Customer Success, Deal Desk, Finance, Billing and Product Engineering. This is a Claude-first role. You'll use Claude every day to do your own work, and the renewal function will be one of the clearest examples inside Anthropic of what AI-run operations look like. What you'll own in your first year The design of the renewal system: which work agents run end to end, which work goes to a person, and the handoff rules between them. A standard renewal that needs no person: a Claude-generated offer in product ahead of term end, accepted and provisioned automatically, with anything outside guidance routed to a seller with a recommended quote. The data the system runs on: contract, commit burndown and usage data clean enough that agents and people trust it, built with Billing and Finance. Early-warning signals for consumption risk and commitment shortfall, and what happens when one fires. The human layer: how internal specialists, outsourced partners and account teams work around the agents, and the measures they're held to. The next large renewal cycles, run with fewer manual steps per renewal than today. Weekly renewal and retention forecasts grounded in usage and contract data. Executive renewal conversations on the largest and most complex accounts, alongside account teams. You may be a good fit if you have Owned renewal, retention or post-sale outcomes at large scale, either running the function or leading the product or service that runs it for others. Led product or engineering teams and shipped software or agents that took over work people used to do. Run or designed a blended model of people, outsourced partners and software, and know where each one breaks. A working grasp of renewal economics: committed and consumption contracts, discount guidance, and the term, billing and CRM data behind them. Built things yourself recently. You can prototype with Claude, read the data and pressure-test an agent's output without waiting on someone else. Set direction with senior executives and held cross-functional teams to it without direct authority. Strong candidates may also have Usage-based pricing and commit burndown experience. Built health, churn or early-warning models that changed what teams did. Worked at a company whose product runs renewals, retention or quote-to-cash for its customers. Worked across regions, including marketplace or cloud-partner billing. Written or spoken publicly about agent-led customer operations. 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: $350,000 — $500,000 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: New York City, NY; 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 As an early member of our Safeguards Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by building and scaling a data driven culture from the ground up. In this unique company, technology, and moment in history, your work will be critical to informing our product and commercial strategy as we deploy safe, frontier AI at scale to the world. You will work closely with product, engineering, policy & enforcement to define and measure key company success metrics, analyze user behavior to identify new enforcement opportunities and build a culture of developing and testing hypotheses through experimentation. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to building robust and scalable systems and processes as our company goes through a phase of rapid growth. Key responsibilities Deep dive into user behavior data to provide insights on safety concerns Define core metrics that measure the team's success. Set goals, build forecasts, monitor performance, and develop actionable reporting Identify and size opportunities to improve the product, influencing product roadmap through your insights and recommendations Develop hypotheses on product changes, design controlled experiments, analyze the results, and make recommendations based on impact to key metrics Build a data driven culture from the ground up by establishing foundational data best practices and making data more accessible across the company Minimum qualifications Expertise in Python, SQL, and data visualization tools. A bias for action and urgency, not letting perfect be the enemy of the effective. A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress. A deep curiosity and energy for pulling the thread on hard questions. Experience in turning open questions and data into concise and insightful analysis. Highly effective written communication and presentation skills. A passion for the company's mission of building helpful, honest, and harmless AI. Preferred qualifications 8+ years of experience in data science or analytics roles, preferably in an infrastructure or operations context. 3+ years of experience deeply embedding in Product teams. Experience working on safety, anti-abuse, integrity shaped problems. 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: $285,000 — $380,000 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: Europe We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones. Currently, we are looking for AI Video Agent Engineer for Elva. Location: Remote Job Type: Full-Time OVERVIEW: We are building an AI-driven video production system designed as an intelligent multi-agent orchestration layer capable of transforming raw ideas and references into fully structured video content. The system operates as a black-box creative engine for different types of users: - professional video creators - casual users - creators of short narrative concepts Users provide an idea, references, or media fragments, and the system automatically orchestrates multiple AI agents responsible for analysis, scripting, editing, and production of video content. We are looking for an engineer who can design and implement multi-agent pipelines, orchestrate AI tools, and build intelligent workflows that combine video analysis, storytelling logic, and automated editing. This role sits at the intersection of AI systems architecture, creative tooling, and multimodal content generation. RESPONSIBILITIES: AI Agent Architecture Design and implement the architecture of a multi-agent video editing system including agents responsible for: - video analysis - narrative generation - editing orchestration - production and output synthesis Define system prompts, behavioral rules, and structured instructions for agents interacting within the pipeline. Pipeline Orchestration (n8n) Develop and maintain complex orchestration pipelines in n8n, including: - multi-agent workflows - tool-calling logic - dynamic routing between tools and models - context passing between agents Pipelines must be capable of selecting the most appropriate models, tools, and strategies depending on the task. Multimodal Data Processing Design robust pipelines for handling: - video materials - image assets - user text prompts - structured metadata Ensure proper data transformation and context transfer across the pipeline stages. Tool & API Integration Integrate both external and internal APIs for multimodal generation and processing, including: - image generation - video generation - speech synthesis - audio generation - video processing services Rapidly evaluate available APIs and select the best quality tools and models for each task. Model Orchestration & Optimization Tune and optimize model interactions, primarily based on Gemini models, including: - prompt engineering - structured outputs - tool-calling workflows - agent collaboration logic Optimize pipelines for quality, reliability, and execution efficiency. Future Architecture (RAG & Knowledge Systems) Design systems that support: - vector databases - retrieval-augmented generation (RAG) - memory and contextual reasoning between agents EXPECTED OUTCOMES: The pipeline system should be capable of: 1. Taking an idea + references as input 2. Analyzing the content 3. Generating a coherent narrative structure 4. Selecting appropriate visual and audio elements 5. Producing a high-quality, structured video output REQUIREMENTS: AI Systems & Agent Architecture Strong experience building multi-agent systems, including: - intent and sub-intent modeling - agent orchestration - agent communication and transport layers - summarization pipelines - context passing between agents Workflow Orchestration Hands-on experience with: - n8n - Agent tool-calling - n8n MCP Experience designing complex automation pipelines is essential. Programming Strong practical coding skills with vibe coding mindset: Primary languages: - Python - JavaScript Bonus experience: - ComfyUI custom nodes - lightweight APIs (e.g., HuggingFace Spaces or inference endpoints) Multimodal Tooling Knowledge Ability to quickly navigate API documentation and integrate tools for: - image generation - video generation - speech synthesis - audio generation - multimodal analysis You should know where and how to obtain the best generation quality for each modality. Creative Thinking - Strong sense of visual rhythm and composition - Creative intuition and storytelling awareness - Good taste in video structure and montage - Ability to evaluate AI-generated output not only by metrics, but also by creative quality and narrative coherence Video & Media Processing Preferred experience with: - FFmpeg - video processing pipelines - image processing workflows NICE TO HAVE: The following qualifications are not mandatory, but will significantly strengthen a candidate’s profile during the evaluation process: Agentic Frameworks Deep understanding of frameworks such as LangGraph and LangChain for building complex cyclic state graphs and stateful agent systems. Advanced RAG & Memory Management Experience designing long-term memory systems for agents, including mechanisms for storing and retrieving successful execution patterns or scenarios to improve future performance through experience-based retrieval. Self-Correction & Reflection Experience building agents with feedback loops such as self-reflection, self-critique, or strategy correction, enabling them to verify their own actions and adapt execution logic dynamically. Evaluation & Observability Experience with tools for monitoring, debugging, and evaluating agent chains and prompt behavior, such as LangSmith, Arize Phoenix, or Promptfoo, with the ability to identify logical failures, quality regressions, and orchestration bottlenecks. IDEAL CANDIDATE: The ideal candidate is someone who naturally operates between engineering and creative production, capable of building systems that automate complex media workflows while preserving narrative coherence and aesthetic quality. You enjoy designing systems where AI agents collaborate to produce meaningful creative outputs. What’s next? If this role sounds like a fit — we’d love to hear from you! Just send over your CV and anything else you’d like us to consider. We’ll review everything within five working days, and if your background matches what we’re looking for, we’ll get in touch to set up a call and get to know each other better.

Location: Singapore 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 As a Regional Research Economist at Anthropic, you will work to collaborate with governments, academia, industry, and civil society in your region to measure and understand AI's effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally-relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system ( Clio ), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. Key responsibilities Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region Advance research collaborations that answer country- or regional-specific economic impact questions Translate research insights into actionable recommendations for policy discussions Make fundamental contributions to the development and expansion of the Anthropic Economic Index , including country/regional-specific analysis Design and collaborate on empirical research on AI's economic effects with governments, academia, industry, and civil society in your region Develop new methodological approaches, in collaboration with partners in your region, for studying AI's impact on: Labor markets and the future of work Productivity and task transformation Economic inequality and displacement Industry-specific disruption and adaptation Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders Minimum qualifications PhD in Economics Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning Demonstrated experience working in and relevant relationships across the region Experience relevant to the study of AI’s impact on the economy, including: Labor market analysis and occupational change Task-based approaches to technological transformation Large-scale data analysis and econometric methods Large language models for social science research Policy-relevant economic research Experimental and quasi-experimental methods for causal inference Macroeconomic modeling and time series forecasting Agent-based modeling or large-scale simulation Technical skills including: Proficiency in Python, R, SQL, or similar tools for large-scale data analysis Experience working with novel datasets and measurement systems Comfort learning new technical tools and frameworks Demonstrated ability to: Lead complex research projects from conception to publication Communicate technical findings to diverse audiences Build relationships across academic, policy, and industry communities Strong interest in ensuring AI development benefits humanity Comfort working with AI systems and ability to think critically about their capabilities and limitations Representative projects How Australia Uses Claude: Findings from the Anthropic Economic Index Anthropic Economic Index Report: Economic Primitives Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption Estimating AI productivity gains from Claude conversations The Anthropic Economic Index Additional information For this role, we're looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI's transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact. 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: London, UK 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 As a Regional Research Economist at Anthropic, you will work to collaborate with governments, academia, industry, and civil society in your region to measure and understand AI's effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally-relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system ( Clio ), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. Key responsibilities Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region Advance research collaborations that answer country- or regional-specific economic impact questions Translate research insights into actionable recommendations for policy discussions Make fundamental contributions to the development and expansion of the Anthropic Economic Index , including country/regional-specific analysis Design and collaborate on empirical research on AI's economic effects with governments, academia, industry, and civil society in your region Develop new methodological approaches, in collaboration with partners in your region, for studying AI's impact on: Labor markets and the future of work Productivity and task transformation Economic inequality and displacement Industry-specific disruption and adaptation Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders Minimum qualifications PhD in Economics Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning Demonstrated experience working in and relevant relationships across the region Experience relevant to the study of AI’s impact on the economy, including: Labor market analysis and occupational change Task-based approaches to technological transformation Large-scale data analysis and econometric methods Large language models for social science research Policy-relevant economic research Experimental and quasi-experimental methods for causal inference Macroeconomic modeling and time series forecasting Agent-based modeling or large-scale simulation Technical skills including: Proficiency in Python, R, SQL, or similar tools for large-scale data analysis Experience working with novel datasets and measurement systems Comfort learning new technical tools and frameworks Demonstrated ability to: Lead complex research projects from conception to publication Communicate technical findings to diverse audiences Build relationships across academic, policy, and industry communities Strong interest in ensuring AI development benefits humanity Comfort working with AI systems and ability to think critically about their capabilities and limitations Representative projects How Australia Uses Claude: Findings from the Anthropic Economic Index Anthropic Economic Index Report: Economic Primitives Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption Estimating AI productivity gains from Claude conversations The Anthropic Economic Index Additional Information For this role, we're looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI's transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact. 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: £195,000 — £245,000 GBP 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: New York City, NY; 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 As part of our growing Data Science & Analytics team, you will play an instrumental role in Anthropic's mission of building safe and beneficial AI — this time by driving data-informed decisions across the commercial customer lifecycle. This role sits at the intersection of fast-moving sales operations and rigorous statistical analysis. You will work across multiple segments and products, partnering with analytics engineers, fellow data scientists, and go-to-market leadership to turn complex commercial data into actionable strategy. You will own measurement and analysis for new logo acquisition through activation, expansion, and retention for a rapidly scaling, consumption-based AI platform. You've worked in cultures of analytical rigor before, and you're eager to help shape the norms and best practices of a growing data science function at a pivotal moment in the company's growth. Key responsibilities Define key metrics, build measurement frameworks, and maintain core reporting to evaluate GTM success across segments and products Analyze commercial and user data to surface actionable insights, size opportunities, and influence roadmaps and go-to-market strategy Develop hypotheses and apply rigorous causal inference methods — controlled experiments, synthetic controls — to make clear, actionable recommendations Investigate anomalies, conduct root cause analyses, and provide data-driven guidance on priorities and decisions Build statistical models, optimization frameworks, and simulations to support and automate commercial decision-making processes Present analyses and recommendations to both technical and non-technical stakeholders, including GTM leadership Establish foundational data practices and help scale analytics infrastructure to support rapid product and commercial iteration Minimum qualifications Proficiency in Python, SQL, and data visualization tools Expertise in experimental design, causal inference, statistical modeling, and A/B testing, particularly in high-scale technical environments Demonstrated ability to translate complex data into clear, actionable insights for both technical and business audiences Strong written communication and presentation skills Ability to work effectively in fast-moving, ambiguous environments — comfortable creating structure and driving progress where neither yet exists Preferred qualifications 5+ years of experience in data science or analytics roles A strong track record in multi-segment, multi-product B2B sales or commercial analytics, especially with consumption-based revenue models Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem Genuine interest in Anthropic's mission of developing safe and beneficial AI 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: $285,000 — $380,000 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: Strava SF Workplace: Hybrid ABOUT STRAVA Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. We are looking for a Staff AI Engineer to join the GenAI + Discovery Platform team at Strava, a team at the core of Strava's AI strategy, responsible for building the shared tooling that enables product teams to ship high value GenAI-powered features at scale. This role sits at the intersection of AI engineering, platform engineering, and server engineering. You will own the systems that make it easy and reliable for all of our product teams to build user facing features on top LLMs at Strava, from shared context, tool management, agent loops, orchestration, data access, search and retrieval to evaluation and ROI frameworks. This is a high-leverage technical role: you're not just building infrastructure, you're building the core understanding of athletes that enable consistent athlete experiences, insight across product surfaces. You'll work closely with product engineers, product managers and data teams to translate cutting-edge AI capabilities into production-ready platforms that facilitate development of AI features that provide value to our athletes. We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco office — three days per week. WHAT YOU'LL DO: - Build for a Well Loved Consumer Product: Work at the intersection of AI and fitness to launch and optimize product experiences that will be used by tens of millions of active people worldwide. - Build the GenAI + Discovery Platform: Set the vision, Design and the shared genAI platform: LLM, and workflow orchestration, prompt management systems, RAG pipelines, search and retrieval services (vector, hybrid and structured search), and evaluation tooling - Enable Teams to Ship AI Features Faster: Build self-serve interfaces and golden paths so that product and CUJ engineering teams can build GenAI-powered features without deep AI expertise. - Own End-to-End AI Capability Delivery: Drive projects from architecture and interface design through production deployment and monitoring, ensuring correctness, latency, reliability, and cost-efficiency of the AI capabilities your platform serves. - Collaborate Across Engineering, and Product: Work closely with engineers and PMs across different verticals to enable the new features and build the genAI roadmap. inform product teams on how to consume and leverage AI capabilities effectively. - Build from a Rich Dataset: Explore and use Strava's extensive unique fitness and geo datasets from millions of users to inform how AI capabilities can extract actionable insights, improve product decisions, and power novel athlete experiences. YOU WILL BE SUCCESSFUL HERE BY: - Treating AI Platform as a Product: Bringing engineering rigor — versioning, contracts, SLAs, monitoring, and deprecation paths — to AI capabilities and LLM integrations that product teams depend on. You don't ship a prototype; you ship a platform. - Leading as an Owner: Taking end-to-end accountability for the reliability and impact of the systems you build, including their correctness in production, their adoption by downstream teams, and the business outcomes they enable. - Building for Leverage: Designing platforms and tooling that multiply the output of the broader team, reducing the AI infrastructure expertise required for CUJ teams to ship GenAI-powered features. - Collaborating Across Disciplines: Working fluidly with ML engineers, data engineers, data scientists, and product managers to align on model selection, evaluation standards, prompt strategies, and consumption patterns. - Raising the Standard: Helping establish best practices for GenAI system development, responsible AI patterns, and operational health, and mentoring teammates at all levels to do the same. - Being passionate about the work you are doing and contributing positively to Strava's inclusive and collaborative team culture and values. WHAT YOU'LL BRING TO THE TEAM: - 5+ years of experience building and operating complex, production AI or backend systems at scale, with a track record of decomposing large technical problems into well-scoped execution across teams. - Demonstrated experience building AI platform tooling or developer-facing infrastructure ideally for LLM or ML systems with a strong instinct for API design, versioning, and self-serve patterns. - Hands-on experience building with large language models in production: agentic workflows, prompt and context engineering, RAG architectures, embedding pipelines, fine-tuning workflows, or LLM evaluation frameworks and tools like Langchain . - Proficiency in search systems (Elasticsearch/OpenSearch, Vector Search, etc) - Proficiency in backend service development on cloud environments (AWS preferred), using Python, Go. Solid understanding of distributed systems and containerized infrastructure (Kubernetes, Docker). - Strong technical leadership: ability to lead multi-team projects, define technical direction, and grow engineers at multiple levels. - Deep curiosity about the evolving GenAI landscape: model capabilities, agent frameworks, multimodal systems: and strong judgment on where and how to apply them to real product problems. - Strong communication and collaboration skills, with the ability to align cross-functional partners around technical direction and build organizational trust in the platforms your team ships. For information on benefits, please click here https://docs.google.com/document/d/e/2PACX-1vTkFMPz3eCjd0FgQ28VWnK4d2BEnzGyaSFGwATR-dQdBb9HxZgay6kboqnT0-V-qaBDzSvYIzI76vT5/pub. WHY JOIN US? Movement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals. Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact. When you join Strava, you’re not just joining a company—you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together. Strava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together. Strava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. California Consumer Protection Act Applicant Notice https://docs.google.com/document/d/e/2PACX-1vSc8y6On4NlP5s12hf4kmWe_pvenVyQ78TbtVaz_clROhj9ADQ6kY4YScglBIuY2joKFKalOReX7vP_/pub

Location: Europe About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. Get Paid to Review Car Damage Photos — Flexible, Remote, Freelance Work Looking for a flexible way to earn extra money on the side? We're hiring freelance contractors to work on a photo review project for a leading European insurance company — and you can do it from anywhere in the EU, on your own schedule. What you'll be doing: Reviewing photos of damaged vehicles and marking the affected areas — things like scratches, dents, cracks, and missing parts — and identifying which part of the car is involved (door, bumper, hood, fender, etc.). Your work directly helps insurance customers receive faster, fairer damage assessments. Full training is provided through clear written guidelines with visual examples. This is a great fit if you have a background in: Auto insurance claims or appraisal Auto body or mechanic work Car dealership or parts experience Any field where identifying vehicle damage and parts is second nature The details: Must be based in the EU 100% remote, work at your own pace Pays roughly €11/hour Project volume is expected to be substantial, with strong potential for increased workload and extended project duration as things scale Freelance/contract work — perfect for picking up extra cash on the side

Location: Europe About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. Get Paid to Review Car Damage Photos — Flexible, Remote, Freelance Work Looking for a flexible way to earn extra money on the side? We're hiring freelance contractors to work on a photo review project for a leading European insurance company — and you can do it from anywhere in the EU, on your own schedule. What you'll be doing: Reviewing photos of damaged vehicles and marking the affected areas — things like scratches, dents, cracks, and missing parts — and identifying which part of the car is involved (door, bumper, hood, fender, etc.). Your work directly helps insurance customers receive faster, fairer damage assessments. Full training is provided through clear written guidelines with visual examples. This is a great fit if you have a background in: Auto insurance claims or appraisal Auto body or mechanic work Car dealership or parts experience Any field where identifying vehicle damage and parts is second nature The details: Must be based in the EU 100% remote, work at your own pace Pays roughly €11/hour Project volume is expected to be substantial, with strong potential for increased workload and extended project duration as things scale Freelance/contract work — perfect for picking up extra cash on the side

Location: New York City, NY; 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 As part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You bring experience from high-bar teams and are eager to help shape the norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world. You’ll be the senior data science leader embedded in our Developer Platform product team and a strategic thought partner to its product leads. You’ll help set product direction for the Claude Developer Platform, spanning our core API, agent orchestration, tool and MCP integrations, and knowledge management capabilities. You’ll bring a point of view on where to invest, how to grow our platform business, and how to deliver more value for the developers and enterprises building on Claude. As a tech lead manager, you’ll also manage a small team of Product Data Scientists, setting their agenda and raising the bar for how data shapes product decisions. Responsibilities: Act as a strategic thought partner to Developer Platform product leads, helping shape product strategy, roadmap priorities, and the major bets the team makes Set the data science agenda for Developer Platform, deciding where the Product Data Science team can have the most impact and what it should deprioritize Manage and develop a small team of Product Data Scientists, coaching them to move from answering questions to shaping decisions Frame the most important and ambiguous questions facing the platform, from how developers and enterprises adopt it to how AI agents are being built and deployed at scale, size the opportunities, and make clear recommendations, including when they challenge the current direction Define how Developer Platform measures success, establishing the core metrics and measurement frameworks that align teams and leadership on what matters Set the standard for experimentation and causal inference across Developer Platform, including where API and B2B products make clean experiments hard, and personally lead the highest-stakes analyses Turn complex analyses into clear narratives and recommendations that drive decisions with senior leadership and cross-functional partners, including go-to-market teams Establish foundational data practices and shape the analytics infrastructure Developer Platform needs to support rapid iteration and decision-making as our products grow You may be a good fit if you: Have extensive experience in data science, including leading analytics for a product area at significant scale Have 3+ years managing data science teams, including setting team direction and developing senior data scientists Have been a trusted partner to senior product and business leaders on API or developer-facing products, with clear examples of changing a roadmap or high-stakes decision Bring strong product sense and business judgment for developer and B2B products, including the ability to frame the right question and take a position with incomplete information Have deep expertise in experimental design, causal inference, and statistical modeling at high scale, with enough fluency in Python and SQL to stay hands-on and guide others’ technical work Communicate clearly in writing and in presentations, including to executive audiences Have a bias for action and thrive in ambiguous, fast-moving environments where you must create clarity and drive progress Care about the company’s mission of building helpful, honest, and harmless AI Strong candidates may also have: Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem 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: $460,000 — $460,000 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 We are hiring Support Engineers to serve as the named, dedicated Product Support point of contact for Anthropic's most strategic enterprise customers. As a Support Engineer, you'll be providing high-touch, deeply contextual support to a defined book of accounts — embedded in your customers' shared channels, known by name to their stakeholders, and partnering closely with Sales, Customer Success, and Applied AI as the technical support voice on the account team. You'll bring deep knowledge of how each of your customers is built on Claude to every interaction, so you can investigate, diagnose, and resolve their most complex technical needs with nuance and speed — and ensure the right internal teams are engaged when needed. Responsibilities Serve as the named technical support contact for a defined book of strategic enterprise accounts, embedded in customer channels and joining recurring account cadences as the support voice Own your customers' technical support needs end to end — investigate, diagnose, and resolve complex issues directly, and partner with internal Engineering and Product teams to drive resolution when needed Build deep, durable context on each customer's architecture, integrations, and use cases so you can respond with nuance rather than from a script Partner closely with the Customer Success Manager, Account Executive, and Applied AI team on each account as part of a single, coordinated account team Capture technical feedback and product friction from your accounts and route it to Product with the impact data and detail needed to prioritize it correctly Manage high-urgency issues for your accounts with extreme ownership, and coordinate cleanly with the broader Product Support team for continuous coverage Help build the foundations of the Support Engineer function — runbooks, escalation paths, tooling, and the metrics we'll use to measure its value Become an expert in all Anthropic products across the API, Claude for Enterprise, and Claude Code You may be a good fit if you Have 5+ years in technical product support, with meaningful time in an escalated, priority, or named-account support team for enterprise customers Have been the person an enterprise customer knows by name and reaches for first when they need technical help Are deeply fluent with APIs and technical SaaS products, and can read technical documentation, error logs, and request traces with ease Have hands-on experience troubleshooting SSO, SAML, OAuth, and enterprise authentication flows Are persistent and curious — you delight in the hunt of tracking down a bug, and are energized by fixing it for every similar user going forward Possess strong user empathy and crisp, kind written communication; you can translate between a frustrated customer engineer and an internal platform team without losing either Are comfortable operating in ambiguity, making informed decisions in never-before-seen situations, and knowing when to pull the escalation cord Enjoy building trust and collaborating closely with go-to-market partners (Sales, CS, Applied AI) without owning the commercial relationship yourself Have contributed to the foundations of a support team before — the essential, often unglamorous work of writing the first runbook Are excited about Anthropic's products and the opportunity to shape how the world's largest companies get support for them Strong candidates may also have SQL proficiency for querying logs and usage data to investigate issues Comfort with command line interfaces and basic scripting (Bash, Python, JavaScript) Understanding of LLM capabilities, prompt engineering patterns, and current limitations Familiarity with enterprise networking concepts, cloud infrastructure (AWS, GCP), and IT environments Experience working inside a customer's shared Slack or similar embedded-support model Background as a Technical Account Manager, Support Engineer, or Designated/Premier Support contact at a developer-platform or infrastructure company 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: $210,000 — $250,000 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 Research Tools team builds systems that support our large-scale, distributed finetuning runs and improve the productivity of researchers. As a manager, you’ll support a team of machine learning and distributed systems experts to make these systems and tools highly efficient, support fast iteration on model development and research, and evolve the infrastructure continuously to incorporate new research advances. Our Research Tooling sits at the intersection of almost every technical group at Anthropic. You’ll work with research teams to incorporate their innovations into our production finetuning pipeline, product teams to help us iterate quickly on customer-oriented model improvements, and infrastructure teams to make sure our training runs and data pipelines are as efficient as possible. About Anthropic: Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and society as a whole. Our interdisciplinary team has experience across ML, physics, policy, business, and product. Responsibilities: Prioritize the team’s work in collaboration with the technical lead, research teams, and product teams to support fast iteration on research projects and training runs. Design processes (e.g., postmortem review, incident response, on-call rotations) that help the team operate effectively. Coach and support your reports to understand and pursue their professional growth. Run the team’s recruiting efforts efficiently, ensuring we can grow as quickly as we need through a period of rapid growth. You may be a good fit if you: Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well. Are an experienced manager (at least 2 years) and actively enjoy people management. Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level) to be effective. Strong candidates may also have: Experience working with research teams, especially as part of a “research to production” pipeline Strong people management experience: Coaching, performance evaluation, mentorship, career development Strong project management skills: Prioritization, communicating across team/org boundaries Experience recruiting for your team: Predicting staffing needs, designing interview loops, evaluating candidates, and closing them 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: $405,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Europe About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. Get Paid to Review Car Damage Photos — Flexible, Remote, Freelance Work Looking for a flexible way to earn extra money on the side? We're hiring freelance contractors to work on a photo review project for a leading European insurance company — and you can do it from anywhere in the EU, on your own schedule. What you'll be doing: Reviewing photos of damaged vehicles and marking the affected areas — things like scratches, dents, cracks, and missing parts — and identifying which part of the car is involved (door, bumper, hood, fender, etc.). Your work directly helps insurance customers receive faster, fairer damage assessments. Full training is provided through clear written guidelines with visual examples. This is a great fit if you have a background in: Auto insurance claims or appraisal Auto body or mechanic work Car dealership or parts experience Any field where identifying vehicle damage and parts is second nature The details: Must be based in the EU 100% remote, work at your own pace Pays roughly €11/hour Project volume is expected to be substantial, with strong potential for increased workload and extended project duration as things scale Freelance/contract work — perfect for picking up extra cash on the side

Location: Munich, Germany 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 As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success Support customers building with both the Claude API and Claude for Work Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases Identify common integration patterns and contribute insights back to our Product and Engineering teams Travel occasionally to customer sites for workshops, technical deep dives, and relationship building Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager Native German speaker with fluent English proficiency Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Comfortable with python Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Deadline to apply: None. Applications will be reviewed on a rolling basis. 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.