Engineering Manager, Context (Agentic Search)

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. About The Role We’re hiring an Engineering Manager to lead Context: the team responsible for the systems and product primitives that give notion’s users and notion agents access to all the relevant context for the task at hand. This includes classic search ranking algorithms and surfaces, but also agentic trajectories with carefully crafted tool calls. You’ll lead a team that focuses on two types of work: reliability of the current context systems and unlocking new contextual capabilities. - We must have a production-grade search product (stability, extensibility, latency, cost). We must ensure search—still a core navigational endpoint—can reliably serve our 100M+ customers. - At the same time, the “agent layer” (how agents interact with search) now accounts for the majority of AI-enabled search traffic (50%+), and is where we expect the fastest iteration and biggest user-facing gains. What You'll Achieve - 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. What You’ll Own - 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 You'll Need to Bring - 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. Bonus Points - 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. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco and New York, the estimated base salary range for this role is $280,000 - $330,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy. #LI-Onsite A Note on AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as

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.

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.