Engineering Manager, Search & Context Platform

About the Role

Notion's Search & Context Platform is the foundational infrastructure that enables 100M+ users and AI agents to discover and reason over the right information. This team owns search infrastructure for lexical and semantic retrieval, platform primitives for managing agent context and memories, and the scalability, performance, security, and enterprise capabilities required for production use at scale.

As Engineering Manager, you'll lead a technically sophisticated team building platform systems that directly support the Search & Context product team and the AI team. You'll establish technical direction, manage platform scope on behalf of internal customers, and balance foundational investments with rapid product iteration while maintaining reliability and security.

Responsibilities

• Lead a platform engineering team responsible for search infrastructure (lexical and semantic retrieval), indexing systems (streaming and batch data pipelines), and context/memory primitives powering Notion's agents
• Develop and communicate a roadmap that balances foundational platform investments—latency, cost, reliability, scalability, freshness, completeness, and enterprise readiness—with fast iteration on new indexing capabilities and agent context features
• Operate the platform with a high reliability bar: define and track SLOs, build deep observability, maintain on-call health, establish early-warning signals, and drive prevention-first incident and post-mortem practices
• Partner closely with the Search & Context product team, AI team, and other platform consumers to define interfaces, capabilities, and service commitments
• Anticipate customer team needs and invest proactively in capacity, capabilities, and platform primitives to accelerate product velocity
• Build and develop the team through hiring, coaching, feedback, and creating an environment where strong technical engineers excel
• Contribute to Notion's broader engineering practices around platform design, reliability engineering, and AI-era infrastructure

Requirements

• 4+ years leading engineering teams with a proven track record of shipping high-quality systems in fast-paced environments
• Technically hands-on management style: stay close to code and design, credibly debate architecture and tradeoffs with senior engineers, and raise technical standards across the team
• Substantial depth in search, retrieval, or large-scale data and indexing systems: lexical search (BM25), semantic search (embeddings, ANN/vector indexes), big data pipelines, hybrid retrieval, ranking, and supporting infrastructure
• Experience product managing a platform or infrastructure scope: evaluate technical architecture and SLAs on behalf of internal customers, manage roadmaps, and make prioritization decisions when customer needs diverge
• Strong systems judgment on scalability, performance, security, build vs. buy decisions, and enterprise readiness; shipped systems optimized for speed, cost, security, and reliability at scale
• Bias toward making hard tradeoffs to unblock product velocity while protecting platform long-term health; comfortable with nuanced yes/no decisions and alternative paths
• Fluent in both technical and product languages; can translate between platform and customer teams effectively
• High tolerance for ambiguity and rapid change in environments where both product surface (agents, AI) and underlying technology (retrieval, LLMs) evolve quickly

Nice to Haves

• Experience building agentic or tool-using systems, or platforms serving LLM-based products
• Familiarity with permissioned, multi-tenant enterprise data: ACL-aware indexing, retrieval, and audit
• Understanding of information retrieval metrics, ranking, or applied machine learning
• Led teams through rapid scope and priority changes and evolving organizational boundaries

Benefits

• Highly competitive cash compensation and equity
• Base salary range for San Francisco: $280,000 - $330,000 per year (based on experience, expertise, role scope, and location)

Location: San Francisco, California (Onsite)