Anthropic
Software Engineer, Labs
$320K–$485K
San Francisco, CA +3 · Full-time · Posted Dec 8, 2025
- Location
- San Francisco, CA
New York City, NY
Seattle, WA
San Francisco, California, United States - Experience
- 8+ years building full-stack applications. Logistics also states that required years correlate with internal job level requirements.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; relevant field of study demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not guaranteed for every role or candidate; if an offer is made, Anthropic will make every reasonable effort to obtain a visa.
About the job
Rapidly prototypes and tests full-stack AI product experiences in Anthropic Labs, translating emerging research capabilities into user-facing concepts and insights for future products.
What you'll do
- Build and ship prototypes; collaborate with researchers to turn model capabilities into intuitive experiences.
- Gather user and partner feedback, run experiments, and evaluate product concepts.
- Document learnings and inform research teams and future product teams.
What they ask for
- 8+ years building full-stack applications, with zero-to-one work in startup or startup-like environments.
- Strong skills across modern web development stacks, with comfort using APIs, databases, and cloud technologies.
- Effective communication and ability to translate complex AI capabilities into intuitive experiences.
- Care about the societal impacts and ethics of the work.
Nice to have
- Experience building products involving AI/ML or large language models, or collaborating with AI/ML research teams.
- User research or usability testing experience; B2B and B2C experience, UI/UX sensibility, or real-time application experience.
Pay
$320,000 — $485,000 USD (base salary)
Tools
React, Node.js, Python
AI focus
Build and test applications showcasing emerging AI capabilities; collaborate with researchers, provide feedback on model effectiveness, and translate capabilities into user experiences.
Model-written summary · the original posting is authoritative