Recruiting Solutions Engineer

Anthropic Anthropic · AI Frontier · San Francisco, CA · People

This role focuses on enabling recruiters to effectively use AI (Claude) in their hiring workflows. It involves educating users, providing technical support, and building prototypes for AI-assisted hiring processes. The engineer will translate recruiter-built skills into reusable assets and design evaluation approaches for these workflows.

What you'd actually do

  1. Serve as the dedicated technical advisor to the Recruiting organization — embedded with recruiters, sourcers, and coordinators to expand what's possible with Claude in real hiring workflows
  2. Lead with education: identify and codify the skills and workarounds recruiters have created, turn them into teachable and reusable assets, and run the enablement motion (sessions, office hours, workshops) that scales them across the org
  3. Work hands-on with recruiters: pairing on prompts, skills, and agent workflows; debugging where things break; turning support patterns into documentation so the same question isn't answered twice
  4. Develop fast prototypes and pilots for high-value workflows that education alone can't solve — built scrappy, validated with real recruiter usage, and designed from day one with a graduation path into People Products' production stack
  5. Collaborate closely with our internal AI governance group (the AI Council) to vet recruiter-built skills into shared tooling, and with People Products to hand off pilots that earn productionization

Skills

Required

  • Software Engineer, Forward Deployed Engineer, Solutions Engineer, or equivalent builder credibility
  • Production experience building LLM-powered applications and workflows
  • prompting
  • context engineering
  • agent architectures
  • evaluation
  • Python
  • TypeScript
  • internal tooling
  • teaching technical concepts to non-technical audiences
  • communication skills

Nice to have

  • recruiting or people technology (Greenhouse, Workday, scheduling and sourcing tools)
  • internal-tools or platform work
  • running enablement programs, workshops, or developer relations-style motions

What the JD emphasized

  • production experience building LLM-powered applications and workflows
  • agent architectures
  • evaluation

Other signals

  • building LLM-powered applications
  • agent architectures
  • evaluation
  • technical enablement