Staff Software Engineer (Labs: Applied AI)

• In this role, you’ll take frontier AI capabilities and turn them into applications that professionals in less software-native roles can pick up and trust — rapidly building and testing new experiences, partnering directly with researchers, domain experts, and users, and generating the insights that shape where this exploration goes next
• Rapidly prototype full-stack applications that bring frontier AI into workflows that have never been software-first, shipping early and often to maximize learning
• Immerse yourself in unfamiliar domains: sit with users, learn how their work actually gets done, and encode that understanding into products, evaluations, and workflows
• Collaborate closely with research teams to understand new model capabilities and translate them into tools that non-technical professionals reach for first
• Work directly with internal teams and external partners across industries to gather feedback, iterate quickly, and validate (or invalidate) product concepts
• Design and run structured experiments to test hypotheses, balancing creative exploration with rigorous evaluation
• Generate documentation and insights to guide successful prototypes toward full product teams
• Provide feedback to research teams about model effectiveness in real-world, domain-heavy settings and where capabilities can improve
• Flexibly contribute across Labs initiatives based on organizational priorities and emerging opportunities — context from one project should inform the next

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents
• Inclusive fertility benefits via Carrot Fertility
• 22 weeks of paid parental leave
• Flexible paid time off and absence policies
• Mental health support for you and your dependents
• Competitive salary and equity packages
• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
• Retirement plans with competitive matching
• Life and income protection plans
• $500/month flexible wellness and time saver stipend
• Commuter benefits
• Annual education stipend
• Home office stipends
• Relocation support for those moving for Anthropic
• Daily meals and snacks in the office- We’re looking for versatile, entrepreneurial engineers who are energized by building for users unlike themselves
• You’ll need to be comfortable with ambiguity, willing to kill your own projects when the data says to, and energized by the pace of building in uncharted territory
• Are a generalist who can transition between different problem spaces as priorities shift
• Can articulate learnings from failed or killed projects without defensiveness; you treat your work as experiments
• Hold strong opinions loosely — you advocate forcefully for ideas but change your mind based on evidence
• Are deeply user-centric — you validate ideas with actual users before over-investing and talk about problems before solutions
• Work independently with good judgment about what matters, without needing constant direction
• Have 8+ years of experience building full-stack applications, with a track record of zero-to-one work in startup or startup-like environments
• Thrive in ambiguity and are energized (not anxious) by uncertainty — you’re comfortable working on projects that might not exist in three months
• Have a hacker mentality: high agency, bias toward shipping, comfort with technical debt when it’s the right tradeoff
• Care about the societal impacts and ethics of your work
• Are deeply curious about how other industries work, and enjoy translating messy, real-world workflows into simple software
• Communicate effectively and can make complex AI capabilities feel intuitive to people who don’t think in software
• Experience collaborating directly with research teams in AI/ML environments
• Background conducting embedded or field-based discovery: user research, interviews, ride-alongs, and usability testing with frontline professionals
• Experience integrating with the systems these industries actually run on (ERPs, EHRs, CRMs, dispatch, scheduling, or point-of-sale systems)
• Experience building products for industries outside of tech — e.g., healthcare, manufacturing, logistics, construction, energy, agriculture, financial services, education, or the public sector
• Hands-on applied AI experience — you’ve built and deployed products powered by AI/ML or large language models
• Required field of study: A field relevant to the role as demonstrated through coursework, traini…