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Updated 2026-06-15 09:00 UTC·© 2025–2026 RoleSuite
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Software Engineer, Knowledge Systems

Exa · San Francisco, California

Exa is an applied AI lab building a search engine unlike the world has ever seen. We build massive-scale infra to crawl the entire web, train state-of-the-art embedding models to process it, and design super high performant vector databases to retrieve over it. We now power search for Cursor, Cognition, HubSpot, and over 400,000 developers and have raised $350m from Lightspeed, Benchmark, and a16z.

 

Our ultimate goal is to build perfect search over all the world's information, far beyond Google. If you want to build massive-scale ML systems that will define the way the new AI world consumes information, this is the place for you.


As a Software Engineer on Knowledge Systems, you’ll help build systems that understand what is true about the world. You’ll work on extracting, connecting, retrieving, and reasoning over knowledge from the web and beyond so AI agents can answer questions with unprecedented precision and completeness.

Desired Experience

  • You have experience building and maintaining complex distributed backend systems

  • You can build data pipelines that process petabytes of documents, metadata, and unstructured data

  • You’re comfortable optimizing systems for correctness, reliability, and scale

  • You care deeply about data quality and finding high-quality information

Plus: experience building systems involving graph traversal, entity resolution, data quality, or truth discovery

Example Projects

  • Build a system that can answer every factual question about every person in the world

  • Design a new query language for searching, traversing, and reasoning over billions of facts

Software pay context

Based on 7,120 disclosed Software salaries on RoleSuite, the role pays a median of $157K/year, with most offers between $123K and $199K (10th–90th percentile: $101K–$235K).

This posting lists $180K–$350K, above the $157K market median.

See the full Software salary breakdown →
Apply →

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