POSITION SUMMARY:
Natera is seeking a Senior Agentic AI Engineer to design, build, and productionize intelligent agent workflows that improve the quality, reliability, and efficiency of our Real-World Data (RWD) clinical extraction platform. Our RWD products transform unstructured and semi-structured clinical documents into structured, research- and care-ready datasets that support oncology and broader clinical use cases.
This role sits at the intersection of applied AI, software engineering, and healthcare data. You will extend a live production pipeline that powers RWD delivery, adding modular AI capabilities that improve what source material reaches extraction, how accurately values are extracted from clinical text, and how uncertain or low-confidence outputs are flagged or corrected before they enter RWD datasets. You will work with limited day-to-day direction defining technical approach and delivering measurable improvements through careful evaluation and phased rollout.
The ideal candidate combines strong hands-on engineering with experience shipping LLM-powered systems in production. This is a senior individual contributor role with high autonomy and end-to-end ownership from design through deployment.
PRIMARY RESPONSIBILITIES
- Design, build, and deploy agent-based AI systems that improve the quality and reliability of clinical data extraction in production.
- Own technical design and delivery for agent workflows.
- Integrate new AI capabilities into existing production platforms with attention to performance, scalability, and cost.
- Partner with clinical AI, engineering, and product teams to prioritize problems, define success metrics, and ship incremental improvements.
- Develop evaluation and monitoring approaches to measure impact, guide iteration, and support safe deployment in a regulated environment.
- Provide technical leadership through clear documentation, design decisions, and pragmatic tradeoffs across accuracy, cost, and delivery timelines.
QUALIFICATIONS
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field; an advanced degree or background in a clinical or life sciences discipline is a plus.
- 7+ years of software engineering experience, including substantial work on production systems at scale.
- 3+ years building and shipping AI/ML-powered applications in production, with hands-on experience in LLM-based systems and multi-step or agent-based LLM workflows — including orchestration, structured outputs, error handling, and integration with downstream systems.
- 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, with AWS strongly preferred; experience with CI/CD, observability, and production support is expected.
- Proven ability to work independently and deliver end-to-end - from technical design through integration and rollout - with strong communication and collaboration across technical and non-technical stakeholders.
- Experience with retrieval-based or document-centric AI systems is strongly preferred.
- Experience in healthcare, life sciences, or other regulated industries is strongly preferred.
KNOWLEDGE, SKILLS, AND ABILITIES
- Python and Object-Oriented Programming
- LLM-Based Systems and Multi-Step or Agent-Based AI Workflows
- Retrieval-Based or Document-Centric AI Systems
- AWS Services, such as S3, SQS, and Lambda/Fargate
- Docker or Container-Oriented Technologies
- REST API and Event-Driven Pipeline Architecture
- Linux Fundamentals
- CI/CD
- Observability and Production Support
- Healthcare or Regulated-Industry Data Environments
- Quality Assurance Mindset