Engineering Manager, People Products

Anthropic is a public benefit corporation dedicated to creating reliable and interpretable AI systems. The Engineering Manager for People Products will lead efforts to build AI-native tools that enhance the employee lifecycle, from hiring to onboarding and beyond, while working closely with internal stakeholders to iterate on solutions.

Responsibilities:

• Build full-stack end-to-end across the People Products portfolio
• Design and implement AI-native workflows: build tools, evals, prompts, and products. You’ll 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, you are expected to talk to your customers
• Make product and architecture decisions independently in a low-structure environment: knowing 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:

• 4+ years of engineering management experience leading high-performing teams in ambiguous, early-stage environments
• Shipped LLM-native features or applications
• Experienced enough to build big features independently, and make great architectural decisions along the way
• Self-sufficient end-to-end: you can go from idea to production without needing a designer, PM, or architect to unblock you
• Move fast without cutting corners: you hold a high quality bar and know how to make smart tradeoffs under time pressure
• Engage directly with users and criticism: you're comfortable talking to internal customers, hearing hard feedback, and incorporating it quickly
• Genuinely mission-driven: you care about the intersection of AI and people practices, not just the technical puzzle
• Collaborative, supportive teammate: you bring people along, communicate clearly about tradeoffs, and make the people around you better
• Bachelor's degree in a related field or equivalent experience
• 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