Software Engineer, Knowledge Engine Query Engine

Software Engineer, Knowledge Engine Query Engine The role owns the query engine that searches a very large knowledge graph spread across several retrieval backends. A strong candidate has worked deep inside a distributed database, search engine or storage system, knows indexing, query planning and storage formats, and is fluent in Go, Rust or C++. The work also calls for distributed systems fundamentals and a habit of profiling before optimizing, with measured latency wins shipped in production. How it fits the AI era The product serves AI models and agents that need fast, precise answers, so the engine must return results at agent speed and at high query volume. AI changes the scale and the kinds of questions asked, but the core engineering stays human: storage layout, cost based planning, consistency during live updates, and judging whether a plan returns correct and complete results. How it builds AI experience Working here means building retrieval infrastructure that AI agents depend on, so the experience gained is in serving machine consumers rather than people. A candidate can prepare by studying how vector, full text, graph and geospatial indexes differ and by practicing query planning and latency profiling on real systems. Familiarity with knowledge graphs and evidence backed claims helps, since the team synthesizes facts from across the web. Worth showing Distributed database internals Query planning and optimization Indexing and storage formats Go, Rust or C++ Latency profiling at scale This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role. About Exa Exa is an applied AI lab that builds a search engine and API for AI models and agents, per the company. #J-18808-Ljbffr