Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Hiring @ 3
LLM @ 3
AI @ 3
- 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.
Details
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The People Products team supports that mission by defining the blueprint for AI at work — hiring, onboarding, teamwork, and promotions — and by building tools that shape Anthropic’s culture and people practices. This role works directly with Claude and internal stakeholders to prototype and ship AI-native products rapidly.
Responsibilities
- Build full-stack end-to-end across the People Products portfolio.
- Design and implement AI-native workflows: build tools, evals, prompts, and products.
- Work directly with internal stakeholders (HR teams, recruiters, managers) to understand problems, gather feedback, and iterate quickly.
- 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
- At least a Bachelor's degree in a related field or equivalent experience.
- Experience shipping LLM-native features or applications and building LLM integrations in production.
- Able to work as a self-sufficient end-to-end engineer: go from idea to production without needing a designer, PM, or architect to unblock you.
- Comfortable engaging directly with internal customers, receiving feedback, and iterating quickly.
- Experience making architectural and product tradeoffs under time pressure while maintaining a high quality bar.
- Familiarity with MCP (Model Context Protocol) or prior experience building Claude/LLM integrations is a plus.
- Background at an AI-native company or in a product-focused 0->1 engineering environment is a plus.
- Experience with HR tech platforms such as Greenhouse, Workday, or Rippling is a plus.
Logistics
- Location: Remote-Friendly (Travel Required) | San Francisco, CA. The company expects staff to be in one of their offices at least 25% of the time (location-based hybrid policy).
- Visa sponsorship: Anthropic states they sponsor visas and retain an immigration lawyer to assist, though sponsorship success may vary by role/candidate.
- Education requirement: Bachelor's degree or equivalent experience.
- Annual Salary: $300,000 - $405,000 USD
Benefits
- Competitive compensation and benefits.
- Optional equity donation matching.
- Generous vacation and parental leave.
- Flexible working hours and a collaborative office space in San Francisco.