Engineering Manager, Search

Anthropic Anthropic · AI Frontier · San Francisco, CA · AI Research & Engineering

Engineering Manager to lead the Search Platform team, responsible for the search stack behind Claude, including indexes, retrieval, ranking, and serving infrastructure. The role involves owning the strategy, roadmap, search quality, and operating the platform at scale, with a product dimension to define search experience. Requires strong technical depth, product mindset, and experience managing engineering teams and search systems.

What you'd actually do

  1. Lead and grow the team of engineers building Anthropic's search platform: indexing, retrieval, ranking and serving
  2. Own the strategy and roadmap for the platform and how Claude's search needs are met over time
  3. Own search quality: evaluation methodology, relevance measurement, regression detection and the ranking improvements they drive
  4. Operate the platform at scale, balancing product traffic against research and training demand while holding a high bar on reliability, latency and cost
  5. Wear the product hat when the work calls for it: prioritize what the search experience needs, sequence launches and represent search in product discussions

Skills

Required

  • Significant experience managing engineering teams, including hiring and growing a team through rapid change
  • Direct experience building or operating search systems at scale: indexing, retrieval, ranking or query serving
  • Enough technical depth to be hands-on when needed; you can review designs, read code and engage credibly with senior ICs
  • A product mindset and comfort making product calls when there isn't a PM in the room
  • A track record of running high-scale, latency-sensitive production systems with real reliability requirements
  • Strong cross-functional skills; you can align product, research and infrastructure partners with different priorities
  • Experience recruiting and closing senior engineers

Nice to have

  • Experience with the economics of search: index freshness, storage and serving costs, quality vs cost tradeoffs
  • Background in embeddings, ranking models or ML-based retrieval
  • Experience migrating traffic off a vendor onto in-house infrastructure
  • Exposure to LLM products and the retrieval demands of large-scale training and inference

What the JD emphasized

  • Direct experience building or operating search systems at scale
  • Enough technical depth to be hands-on when needed
  • A product mindset and comfort making product calls when there isn't a PM in the room
  • Experience recruiting and closing senior engineers

Other signals

  • leading a team of engineers
  • building search stack
  • retrieval and ranking systems
  • serving infrastructure
  • operating at scale
  • product dimension
  • hands-on technical leadership