Description
Who We Are The Search Systems team at MongoDB builds the core infrastructure behind MongoDB Search and Vector Search. Our mission is to make advanced search capabilities feel native to the database, so developers can build powerful, scalable applications without standing up separate systems or compromising transactional performance. We are the team behind mongot, the indexing and query execution engine that powers Search and Vector Search across MongoDB Atlas and self-managed deployments.
Our work sits at the intersection of distributed systems, databases, and search infrastructure. We integrate Apache Lucene with MongoDB using native query operators like $search and $vectorSearch, build asynchronous change-stream-driven indexing pipelines that scale independently from transactional workloads, and support deployments across cloud, on-prem, and hybrid environments. Engineers on this team own meaningful subsystems, influence architectural decisions, and work on core database technology used by developers globally.
This role can be based out of our Toronto office or remotely in Canada. What You'll Do This is a rare opportunity to set the technical direction for one of MongoDB's most strategic investments. You will define the architecture of a self-contained search system that spans Community, Enterprise, and Atlas, while guiding how we integrate AI-native capabilities from Voyage AI.
This is not a chance to influence a feature. It is a chance to shape the foundation of how developers everywhere build applications with MongoDB. In this role, you will: Own the cross-system data infrastructure layer for MongoDB's next-generation Search and Vector Search capabilities, carrying outcomes that span 6-18 months Define the technical roadmap for Atlas Search, identifying gaps, proposing solu
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