Principal AI Engineer

Natera

4h

About The Position

Natera is seeking a Principal AI Engineer to set technical direction for and hands-on build of the Vector Store GenAI Platform, which powers document intelligence and retrieval across its Real-World Data organization. The platform ingests clinical documents from multiple sources, indexes them for high-quality search, and makes the content available to downstream AI workflows and business use cases across oncology and other clinical domains.

This principal-level individual contributor role owns architecture and implementation of retrieval, document processing, and ingestion systems. The engineer will define platform strategy and sequencing, ship production code in a cloud environment, improve search and retrieval reliability and quality, and validate approaches through proofs of concept and benchmarks. In partnership with clinical, engineering, and product leaders, the role turns ambiguous priorities into a technical roadmap, establishes standards for retrieval used by agents and re-extraction workflows, and delivers measurable improvements in platform quality and operability with high autonomy and limited day-to-day direction.

The role calls for deep hands-on engineering and end-to-end ownership of complex AI platforms: setting direction, implementing critical-path work, and raising the technical bar across teams that consume and extend the platform.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• 10+ years of software engineering experience, including substantial ownership of production systems at scale.
• 5+ years building and shipping AI/ML-powered applications in production, with hands-on experience in retrieval-augmented systems, vector search, and document-centric AI pipelines, including indexing, retrieval quality, evaluation, and integration with downstream LLM or agent systems.
• Demonstrated experience as a principal or equivalent individual contributor: setting technical direction for a platform or multi-team capability, making durable architecture decisions, and personally delivering critical-path production code.
• Strong hands-on expertise in Python and modern software engineering practices, including testing, code review, workflow orchestration, and agile delivery in large existing codebases.
• Experience designing and operating AI systems in cloud environments; experience with CI/CD, observability, and production support.
• Ability to work independently as an architecture-plus-build individual contributor, influence without direct authority, align stakeholders, and deliver end-to-end from strategy through integration and rollout.
• Strong communication skills across technical and non-technical audiences.

Nice To Haves

• Advanced degree or background in a clinical or life sciences discipline.
• AWS experience; AWS is strongly preferred.
• Experience with clinical or structured healthcare documents and document-centric search or RAG systems.
• Experience in healthcare, life sciences, or other regulated industries.
• Experience designing retrieval interfaces used by agents or multi-step LLM workflows.

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 for downstream AI workflows.
• Set technical direction for hybrid search and retrieval quality; evaluate embedding models and retrieval approaches through implementations, proofs of concept, and benchmarks, and drive effective approaches into production.
• Improve document parsing and chunking so clinical content supports accurate, structured, and faceted retrieval across common document types.
• Define and build stable, reproducible retrieval for agent and re-extraction workloads, including durable content identifiers, flexible context assembly, versioned indices, and quality or confidence signals.
• Strengthen document classification and ingestion visibility so source material is discoverable, operable, and measurable at scale across historical and ongoing data flows.
• Improve retrieval quality through better deduplication, clinical concept normalization, and exploration of retrieval methods where they add clear value.
• Integrate LLM capabilities into production systems with attention to performance, scalability, cost, observability, and safe operation in a regulated environment.
• Partner with clinical AI, engineering, product, and subject-matter expert stakeholders to prioritize workstreams, define success metrics, and sequence roadmap investments without disrupting the live platform.
• Provide principal-level technical leadership through architecture decisions, design reviews, documentation, mentoring influence, and pragmatic tradeoffs among accuracy, latency, cost, and delivery timelines.

Benefits

• Comprehensive medical, dental, vision, life, and disability plans for eligible employees and their dependents.
• Free testing for Natera employees and their immediate families.
• Fertility care benefits.
• Pregnancy and baby bonding leave.
• 401k benefits.
• Commuter benefits.
• Employee referral program.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal