Anthropic
Engineering Manager, Search
$320K–$405K
San Francisco, CA +2 · Manager · Full-time · Posted Aug 3, 2026
- Location
- San Francisco, CA
New York City, NY
San Francisco, California, United States - Experience
- Years of experience required will correlate with the internal job level requirements for the position.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; relevant field of study demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; if an offer is made, Anthropic will make every reasonable effort to obtain a visa.
About the job
Leads Anthropic’s Search Platform team, setting strategy and building and operating the indexing, retrieval, ranking, and serving systems behind Claude search.
What you'll do
- Lead and grow the engineering team; recruit, hire, and retain engineers.
- Own platform strategy, search quality, and reliable operation at scale, balancing product, research, and training demand.
- Set product priorities and collaborate with product, research, and infrastructure teams; contribute hands-on to technical reviews and investigations.
What they ask for
- Significant experience managing engineering teams, including hiring and growing teams through rapid change.
- Direct experience building or operating search systems at scale.
- Technical depth to review designs, read code, and engage with senior individual contributors.
- Track record operating high-scale, latency-sensitive production systems with reliability requirements; strong product and cross-functional skills.
Nice to have
- Experience with search economics, including index freshness, storage, serving costs, and quality-cost tradeoffs.
- Background in embeddings, ranking models, or ML-based retrieval; experience migrating vendor traffic in-house; or exposure to LLM products and large-scale training and inference retrieval.
Pay
$320,000 — $405,000 USD (base salary)
Tools
Claude, embeddings, ranking models, ML-based retrieval
AI focus
Builds search and retrieval systems supporting Claude and research workloads, including retrieval demands for large-scale training and inference.
Model-written summary · the original posting is authoritative