Note: The job is a remote job and is open to candidates in USA. Notion is the collaborative AI workspace where teams and agents think together. They are seeking an Engineering Manager to lead the Context team, responsible for enhancing search capabilities and ensuring reliability for users and agents alike.
Responsibilities
- Build and lead a high-performing team responsible for context, memories, and ranking that power agent workflows across Notion
- Drive a roadmap that improves the end-to-end reliability of agents acquiring context across Notion + connectors
- Raise the bar on context quality through evaluation + experimentation, and ship improvements that move core user metrics
- Balance foundational platform work (latency, cost, stability) with rapid iteration on new agentic capabilities
- Partner deeply across AI, product, infra, and partner ecosystems to unblock delivery and set clear ownership boundaries
- Direction and execution for Context as both a product and a platform
- Agentic retrieval approaches that treat 'finding' as a sequence of actions (tool use, query generation, iterative retrieval), not a single ranked list
- A durable measurement loop: evaluation frameworks, instrumentation, and experimentation practices to improve functional correctness and user-perceived usefulness
- Team health and talent: hiring, coaching, feedback, growth, and performance management
Skills
- Experience leading engineering teams working on search/retrieval/relevance, AI product, or adjacent platform problems
- Experience building agentic or tool-using systems
- Strong product + systems judgment in ambiguous environments; can make crisp tradeoffs and keep execution moving
- Comfort owning a roadmap that requires heavy cross-team coordination and stakeholder alignment
- Sufficient technical depth in modern retrieval (lexical + semantic, embeddings, reranking) and where LLMs fit (query generation, tool orchestration, evidence selection)
- Track record building collaborative, supportive, and high-expectation team cultures
- High tolerance for ambiguity and change; enjoys learning quickly and adapting plans
- Experience with multi-source retrieval and permissioned enterprise data
- Experience establishing eval frameworks for AI/agent outcomes
- Experience with classic information retrieval metrics and machine learning techniques
- Has led teams through rapid scope changes and evolving org boundaries
Benefits
- Highly competitive cash compensation
- Equity
- Benefits
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