POSITION SUMMARY Natera is seeking a Principal AI Engineer to set technical direction for, and hands-on build of, the Vector Store GenAI Platform that powers document intelligence and retrieval across our Real-World Data (RWD) organization. The platform ingests clinical documents from multiple sources, indexes them for high-quality search, and makes that content available to downstream AI workflows and business use cases across oncology and other clinical domains. This is a principal-level individual contributor role with architecture-plus-build ownership of retrieval, document processing, and ingestion systems. You will define platform strategy and sequencing, ship production code in a cloud environment, raise the reliability and quality of search and retrieval, and prove new approaches through POCs and benchmarks. You will partner with clinical, engineering, and product leaders to turn ambiguous priorities into a clear technical roadmap, establish standards for how retrieval serves agents and re-extraction workflows, and deliver measurable improvements in platform quality and operability—with high autonomy and limited day-to-day direction. The ideal candidate combines deep hands-on engineering with a track record of owning complex AI platforms end to end. You set direction, implement critical path yourself, and elevate the technical bar across the teams that consume and extend the platform. RESPONSIBILITIES Own platform architecture and hands-on delivery for the Vector Store GenAI Platform, including search and retrieval, document processing and chunking, ingestion pipelines, and APIs that serve downstream AI workflows. Set technical direction for hybrid search and retrieval quality; evaluate embedding models and retrieval approaches through working implementations, POCs, and benchmarks, and drive adoption of what works in production. Advance document parsing and chunking so clinical content is indexed in a way that supports accurate, structured, and faceted retri
Role overview
Job description
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework
…What they are looking for
Skills & requirements
Qualification
A track record of eval-driven product improvement: you have diagnosed agent or LLM behaviour from traces and user feedback, designed the evaluation that exposed the problem, shipped the fix and measured the outcome; Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation; If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role
Department · Enterprise Search - Engineering
Hiring company
Elastic
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C$128.3K – C$203K/yr
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