Engineering Manager, Search & Context Platform
Listed on 2026-06-15
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Software Development
AI Engineer (Applied/Software)
Who We Are
Notion is the collaborative AI workspace where teams and agents think together. 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. Millions of individuals, small teams, and large companies run their work on Notion.
Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. 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.
Notion's Search & Context Platform is the substrate that powers how 100M+ users and, increasingly, Notion's agents find and reason over the right information. This team owns the search infrastructure and indexing systems powering lexical and semantic retrieval, the platform primitives for managing agent context and memories
, and the scalability, performance, security, and enterprise capabilities that make all of it production-grade.
Data growth is faster than ever, and the systems that power this need to rapidly evolve to support an order of magnitude growth—both in the volume of content we index and in the load that agents now place on the retrieval layer.
As the Engineering Manager for this team, you'll lead a technically deep group of engineers building platform systems used by multiple product teams. Your most important customers are the Search & Context product team and the AI team (building agents on top of these primitives). You'll set the technical direction, product manage the platform scope on behalf of those customers, and make hard tradeoffs to move fast in service of product velocity — while keeping the platform sustainable, reliable, and secure.
WhatYou'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 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.
- Staying ahead of the needs of your customer teams by anticipating where the product is going, investing in capacity, capabilities, and primitives and making 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.
- 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
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