engineering
Posted YesterdayEngineering Manager, Search & Context Platform
at Notion
San Francisco, United StatesHybrid
Responsibilities
- - Build and lead the team through hiring, coaching, feedback, growth, and creating an environment where strong technical ICs do their best work.
Requirements
- We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented.
- Each and every team of Notinos is working to set the standard for how humans work together in the AI era.
- From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work.
- Your most important customers are the Search & Context product team and the AI team (building agents on top of these primitives).
- - Operate the platform with a high reliability bar: SLOs, deep observability, on-call health, early-warning signals, and prevention-first incident/post-mortem practices and drive measurable improvements to search and context quality, performance, and reliability for Notion's largest customers and o - 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.
- - Contribute to Notion's broader engineering practices around platform design, reliability, on-call, and AI-era infrastructure.
- 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 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.