Engineering Manager, Search & Context Platform

What You'll Achieve

• Lead a high-performing platform team responsible for search infrastructure (lexical & semantic), indexing (including streaming & batch data pipelines), retrieval (lexical + semantic + hybrid), and the context/memory primitives that power Notion's agents.
• Set a clear roadmap that balances foundational platform investments (latency, cost, reliability, scalability, freshness, completeness, security, enterprise readiness) with fast iteration on indexing new entities/features and building new context capabilities for agents.
• Operate the platform with a high reliability bar: SLOs, deep observability, on-call health, early-warning signals, and prevention-first incident/post-mortem practices.
• Drive measurable improvements to search and context quality, performance, and reliability for Notion's largest customers.
• Partner and build closely with the Search & Context product team, the AI team, and other consumers of the platform on the right interfaces, capabilities, and commitments.
• Anticipate where the product is going, invest in capacity, capabilities, and primitives, and make sure the platform accelerates product velocity.
• Build and lead the team through hiring, coaching, feedback, growth, and creating an environment where strong technical ICs do their best work.
• Contribute to Notion's broader engineering practices around platform design, reliability, on-call, and AI-era infrastructure.

Skills You'll Need to Bring

• 4+ years of experience leading engineering teams with a track record of shipping high-quality systems in a fast-paced environment.
• A technically leaning management style—you stay close to the code and the design, can credibly debate architecture and tradeoffs with senior ICs, and raise the technical bar of your team.
• Sufficient depth in search, retrieval, or large-scale data/indexing systems: lexical search (e.g. BM25), semantic search (embeddings, ANN/vector indexes), big data pipelines, hybrid retrieval, ranking, and the surrounding infrastructure.
• Experience product managing a platform or infrastructure scope: continuous evaluation of technical architecture, SLAs, and a roadmap on behalf of internal customer teams, and making prioritization calls when those customers want different things.
• Strong systems judgment around scalability, performance, security, build vs buy and enterprise readiness—you've shipped systems that had to be fast, cheap, secure, and reliable at scale, not just functional.
• A bias for making hard tradeoffs to unblock product velocity while protecting the long-term health of the platform; comfortable saying "yes, with these constraints" or "no, here's the better path."
• Experience working closely with product and AI teams as customers of a platform—you can speak both languages and translate between them.
• High tolerance for ambiguity and rapid change; you enjoy operating in a space where both the product surface (agents, AI) and the underlying technology (retrieval, LLMs) are evolving quickly.

Nice to Haves

• Experience building agentic or tool-using systems, or platforms that serve LLM-based products.
• Familiarity with permissioned, multi-tenant enterprise data—ACL-aware indexing, retrieval, and audit.
• Understanding of classic information retrieval metrics, ranking, or applied ML.
• Has led teams through rapid scope and priority changes and evolving org boundaries.