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AnthropicSan Francisco, CA | New York City, NY
Engineering Manager (Search)
On-siteFull Time$320k - $405k per yearPosted 25 days ago
About the role
- Anthropic is looking for an Engineering Manager to lead the Search Platform team. This team builds the search stack behind Claude: the indexes, retrieval and ranking systems and serving infrastructure that power web search across claude.ai, the API and agentic surfaces
- Search is core to how Claude answers questions about the world, and the team owns both the problem and the solution end to end: growing the index, improving retrieval quality and running the serving stack at production scale. The same platform also serves research workloads, so demand comes from multiple user surfaces, often at the same time
- The role carries a product dimension. Search sits close to the user experience and PM coverage is thin at times, so often the EM helps decide what a good search experience looks like, not just how to build it. You’ll partner with product teams shipping search-backed features, research teams that depend on retrieval quality and capacity, and the infrastructure teams that run the systems underneath
- We’re looking for someone with real search experience who can be hands-on when needed: reviewing designs, digging into relevance regressions and holding their own in technical debates
- Lead and grow the team of engineers building Anthropic’s search platform: indexing, retrieval, ranking and serving
- Own the strategy and roadmap for the platform and how Claude’s search needs are met over time
- Own search quality: evaluation methodology, relevance measurement, regression detection and the ranking improvements they drive
- Operate the platform at scale, balancing product traffic against research and training demand while holding a high bar on reliability, latency and cost
- Wear the product hat when the work calls for it: prioritize what the search experience needs, sequence launches and represent search in product discussions
- Drive cross-team collaboration with product, research and infrastructure partners; articulate dependencies, risks and progress clearly
- Be hands-on where it matters: design reviews, incident follow-ups and the occasional deep dive into why relevance moved
- Recruit, close and retain strong engineers in a competitive market Benefits
- Comprehensive health, dental, and vision insurance for you and your dependents
- Inclusive fertility benefits via Carrot Fertility
- 22 weeks of paid parental leave
- Flexible paid time off and absence policies
- Mental health support for you and your dependents
- Competitive salary and equity packages
- Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
- Retirement plans with competitive matching
- Life and income protection plans
- $500/month flexible wellness and time saver stipend
- Commuter benefits
- Annual education stipend
- Home office stipends
- Relocation support for those moving for Anthropic
- Daily meals and snacks in the office
- Enough technical depth to be hands-on when needed; you can review designs, read code and engage credibly with senior ICs
- Strong cross-functional skills; you can align product, research and infrastructure partners with different priorities
- Interest in AI safety and Anthropic’s mission
- Direct experience building or operating search systems at scale: indexing, retrieval, ranking or query serving
- A product mindset and comfort making product calls when there isn’t a PM in the room
- Experience recruiting and closing senior engineers
- A track record of running high-scale, latency-sensitive production systems with real reliability requirements
- Significant experience managing engineering teams, including hiring and growing a team through rapid change
- 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
- Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
- Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
- We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed
- Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you’re interested in this work