Staff Software Engineer, People Products

at Anthropic

📍 San Francisco, United States

USD 320,000-405,000 per year

SENIOR

✅ Hybrid

✅ Visa Sponsorship

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 6 LLM @ 3

Details

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The People Products team exists to support Anthropic’s mission by defining the blueprint for AI at work. The team supports the employee lifecycle from hiring to onboarding, teamwork, and promotions.

Responsibilities

Build full-stack end-to-end across the People Products portfolio.
Design and implement AI-native workflows: build tools, evals, prompts, and products. Help define what is possible in applied AI for people processes.
Work directly with internal stakeholders — HR teams, recruiters, managers — to understand problems, gather feedback, and iterate quickly without waiting for requirements to be handed down. No gatekeeping; expected to talk to internal customers.
Make product and architecture decisions independently in a low-structure environment: know when to cut scope, when to ship, and when to ask for input.
Contribute ideas for how the team works, what it builds, and where applied AI can have the most leverage in people workflows.

Requirements

8+ years of relevant experience as a Fullstack or product engineer, with a track record of leading complex, multi-month projects or teams as a tech lead or equivalent.
Shipped LLM-native features or applications.
Able to build big features independently and make architectural decisions.
Self-sufficient end-to-end: can go from idea to production without needing a designer, PM, or architect to unblock you.
Move fast without cutting corners: maintain a high quality bar and make smart tradeoffs under time pressure.
Comfortable engaging directly with users and criticism, and incorporating hard feedback quickly.
Mission-driven: care about the intersection of AI and people practices.
Collaborative, supportive teammate: communicate clearly about tradeoffs and help improve others.

Strong Candidates May Also Have

Familiarity with MCP (Model Context Protocol) or prior experience building Claude or LLM integrations in production.
Background at an AI-native company or in a product-focused 0->1 engineering environment.
Experience with HR tech platforms such as Greenhouse, Workday, or Rippling.

Logistics

Location-based hybrid policy: currently expected that all staff are in one of the offices at least 25% of the time (some roles may require more time in offices).
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 correlates with internal job level requirements for the position.
Visa sponsorship: Anthropic does sponsor visas; if an offer is made, it will make every reasonable effort to get a visa and retains an immigration lawyer to help.