Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 6
API
Communication @ 7
Hiring @ 4
LLM @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic is looking for an Engineering Manager to lead the Search Platform team. The team builds the search stack behind Claude, including indexes, retrieval and ranking systems, and serving infrastructure that powers web search across Claude, the API, and agentic surfaces.
Search is responsible for growing the index, improving retrieval quality, and operating the serving stack at production scale. The platform also supports research workloads, with demand from multiple user surfaces at the same time. The role includes a product dimension, requiring the manager to help define the search experience, prioritize work, and partner with product, research, and infrastructure teams.
The successful candidate should have significant search experience and be able to remain hands-on when needed, including reviewing designs, investigating relevance regressions, and participating in technical discussions.
Responsibilities
- Lead and grow the engineering team building Anthropic's search platform, including indexing, retrieval, ranking, and serving.
- Own the platform strategy and roadmap and determine how Claude's search needs are met over time.
- Own search quality, including evaluation methodology, relevance measurement, regression detection, and ranking improvements.
- Operate the platform at scale while balancing product traffic with research and training demand and maintaining high standards for reliability, latency, and cost.
- Help define the search product experience, prioritize work, sequence launches, and represent search in product discussions.
- Drive collaboration with product, research, and infrastructure partners and clearly communicate dependencies, risks, and progress.
- Participate hands-on in design reviews, incident follow-ups, and deep dives into relevance changes.
- Recruit, close, and retain strong engineers.
Requirements
- Significant experience managing engineering teams, including hiring and growing a team through rapid change.
- Direct experience building or operating search systems at scale, including indexing, retrieval, ranking, or query serving.
- Sufficient technical depth to review designs, read code, and engage credibly with senior individual contributors.
- A product mindset and comfort making product decisions when a product manager is not present.
- A track record of running high-scale, latency-sensitive production systems with significant reliability requirements.
- Strong cross-functional communication and collaboration skills.
- Experience recruiting and closing senior engineers.
- Interest in AI safety and Anthropic's mission.
- Preferred experience with search economics, including index freshness, storage and serving costs, and quality-versus-cost tradeoffs.
- Preferred background in embeddings, ranking models, or machine-learning-based retrieval.
- Preferred experience migrating traffic from a vendor to in-house infrastructure.
- Exposure to LLM products and the retrieval demands of large-scale training and inference.
- A bachelor's degree or equivalent combination of education, training, and experience. The field of study should be relevant to the role through coursework, training, or professional experience.
Benefits
Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office spaces for collaboration.