Staff Software Engineer, Labs: Applied AI at Anthropic

On-site - San Francisco, CA, USA

Anthropic is building AI systems that are safe, beneficial, and transformative. The Staff Software Engineer in Labs: Applied AI will take frontier AI capabilities and turn them into applications for professionals in non‑software‑native roles, rapidly prototyping full‑stack solutions, collaborating with research teams, and gathering user feedback to guide product direction. This role requires a versatile, entrepreneurial engineer comfortable with ambiguity and a strong focus on user experience, safety, and societal impact.

Salary

USD 320,000 - 405,000

Requirements

Skills

8+ years of experience building full-stack applications with zero-to-one work in startup or startup-like environments
deep curiosity about how other industries work and ability to translate messy real-world workflows into simple software
thrives in ambiguity and is energized by uncertainty
hacker mentality: high agency, bias toward shipping, comfort with technical debt when appropriate
user‑centric: validates ideas with actual users before over‑investing
ability to articulate learnings from failed or killed projects without defensiveness
holds strong opinions loosely and advocates forcefully for ideas while changing mind based on evidence
generalist who can transition between different problem spaces as priorities shift
works independently with good judgment about what matters, without constant direction
effective communication skills and can make complex AI capabilities intuitive to non‑software users
care about societal impacts and ethics of work
Bachelor’s degree or an equivalent combination of education, training, and/or experience

Responsibilities

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 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 for non‑technical professionals
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

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