Staff Software Engineer, People Products na Anthropic

Remoto - San Francisco, CA, United States

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Anthropic is growing fast and looking for a Staff Software Engineer for People Products to build AI-native tools for hiring, onboarding, teamwork, and promotions. The role involves full-stack development, product and architecture decisions, cross‑functional collaboration, and autonomy in a low‑structure environment, supporting the company’s mission to create reliable, interpretable, and steerable AI systems.

Salary

USD 320,000 - 405,000

Requirements

Skills

  • 8+ years of relevant experience as a Fullstack or product engineer
  • Track record of leading complex, multi-month projects or teams as a tech lead or equivalent
  • Shipped LLM-native features or applications
  • Experienced enough 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
  • Move fast without cutting corners; holds a high quality bar and makes smart tradeoffs under time pressure
  • Engage directly with users and criticism; comfortable talking to internal customers
  • Genuinely mission-driven; cares about the intersection of AI and people practices
  • Collaborative, supportive teammate; brings people along, communicates clearly about tradeoffs
  • 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

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 without gatekeeping
  • Make product and architecture decisions independently in a low-structure environment
  • Contribute ideas for how the team works, what it builds, and where applied AI can have the most leverage in people workflows

Technologies

ClaudeMCPLLMGreenhouseWorkdayRippling

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