Engineering Manager, Search (AI)

TL;DR

Engineering Manager, Search (AI): Leading the Search Platform team to build indexes, retrieval, and ranking systems for Claude with an accent on scalability and retrieval quality. Focus on optimizing the search stack, balancing product and research demands, and defining the search user experience.

Location: Hybrid (San Francisco, CA or New York City, NY). Staff are expected to be in one of the offices at least 25% of the time.

Salary: $320,000 - $405,000 USD per year

Company

Anthropic is a public benefit corporation focused on creating reliable, interpretable, and steerable AI systems that are safe and beneficial for society.

What you will do

• Lead and grow the search platform team focusing on indexing, retrieval, ranking, and serving.
• Own the strategy and roadmap for how Claude's search capabilities evolve over time.
• Manage search quality through evaluation methodology, relevance measurement, and regression detection.
• Operate high-scale production systems, balancing product traffic with research and training demand.
• Define the search user experience and prioritize feature launches in collaboration with product teams.
• Recruit, close, and retain high-performing engineers in a competitive market.

Requirements

• Significant experience managing engineering teams, including hiring and scaling through rapid change.
• Direct experience building or operating large-scale search systems (indexing, retrieval, ranking, or query serving).
• Technical depth to conduct design reviews, read code, and engage with senior ICs.
• Proven track record of running latency-sensitive production systems with strict reliability requirements.
• Strong cross-functional skills to align product, research, and infrastructure partners.
• Must be based in or able to work from San Francisco, CA or New York City, NY to comply with hybrid office policies.

Nice to have

• Experience with search economics, including index freshness, storage, and serving cost tradeoffs.
• Background in embeddings, ranking models, or ML-based retrieval.
• Experience migrating search traffic from vendor solutions to in-house infrastructure.
• Exposure to LLM products and the specific retrieval demands of large-scale training and inference.

Culture & Benefits

• Competitive compensation and benefits with optional equity donation matching.
• Generous vacation and parental leave policies.
• Flexible working hours and high-quality collaborative office spaces.
• Commitment to AI safety and a highly collaborative, empirical approach to research.
• Visa sponsorship availability for qualified candidates.