AI Engineer
natera • US Remote
Posted: May 21, 2026
Job Description
AI Engineer, Provider & Oncology Innovation
Location: US Remote
The Role
This is a high-autonomy, high-agency position for a builder who thrives in ambiguity and wants to ship AI products that directly impact cancer care. You'll sit at the intersection of engineering, product, and design, working across all three modalities to ship products to customers. Your work will span two critical domains:
1. AI Products for Providers
Design and ship AI-powered experiences for oncologists and clinical teams. This includes exploring conversational AI experiences, building agent-based workflows that help providers navigate managing patient care, and bringing new clinical AI products to market. You'll spend meaningful time with customers to deeply understand their workflows and uncover where AI can create transformative value.
2. Commercializing Natera's AI Foundation Models
You'll be the bridge between Natera's AI research lab and the launched product. Our team has developed proprietary models that need to be brought to market and into the hands of clinicians. You'll contribute to training and post-training of these models, build the serving infrastructure, shape the user experience, and own the end-to-end deployments of these products.
What You'll Do
-
Ship zero-to-one AI products end-to-end — from customer discovery and prototyping through production deployment and iteration
-
Build agentic AI systems — design and implement autonomous and semi-autonomous workflows using LLMs, tool-use, memory, and orchestration
-
Develop AI tools that improve efficiency across clinical operations, data extraction, manual workflows, and more
-
Commercialize AI research — partner with the AI lab to take proprietary models from research prototypes and into production
-
Contribute to model training and post-training — fine-tuning, evaluation, safety testing, and optimization of Natera's proprietary oncology models
What We're Looking For
Required
-
5+ years of software engineering experience, with at least 2 years focused on AI/ML or LLM-powered products in production
-
Demonstrated ability to ship end-to-end — you've taken AI features or products from idea to production, ideally in a zero-to-one context
-
Strong full-stack engineering skills — proficiency in Python and modern web frameworks; you can build both the model pipeline and the user-facing product
-
Production experience with LLMs — fine-tuning, RAG, prompt engineering, agentic architectures, structured extraction, evaluation, and observability
-
High agency and autonomy — you don't wait for permission, detailed specs, or hand-holding. You unblock yourself, seek out the highest-impact work, and drive it to completion
-
Excellent communication — you can translate complex AI concepts for clinical and business stakeholders, and articulate a vision for what you're building and why
Preferred
-
Experience in healthcare, biotech, diagnostics, or pharma — especially oncology
-
Familiarity with clinical workflows, electronic health records, or provider-facing software
-
Track record of working in regulated environments (HIPAA, FDA, CLIA, CAP)
-
Background in or comfort with computational biology, genomics, or multimodal data (imaging, sequencing, clinical records)
-
Experience with AWS infrastructure, Kubernetes, MLflow, or similar ML platform tooling
-
Prior experience in a high-growth startup or zero-to-one product environment
Additional Content
AI Engineer, Provider & Oncology Innovation
Location: US Remote
The Role
This is a high-autonomy, high-agency position for a builder who thrives in ambiguity and wants to ship AI products that directly impact cancer care. You'll sit at the intersection of engineering, product, and design, working across all three modalities to ship products to customers. Your work will span two critical domains:
1. AI Products for Providers
Design and ship AI-powered experiences for oncologists and clinical teams. This includes exploring conversational AI experiences, building agent-based workflows that help providers navigate managing patient care, and bringing new clinical AI products to market. You'll spend meaningful time with customers to deeply understand their workflows and uncover where AI can create transformative value.
2. Commercializing Natera's AI Foundation Models
You'll be the bridge between Natera's AI research lab and the launched product. Our team has developed proprietary models that need to be brought to market and into the hands of clinicians. You'll contribute to training and post-training of these models, build the serving infrastructure, shape the user experience, and own the end-to-end deployments of these products.
What You'll Do
-
Ship zero-to-one AI products end-to-end — from customer discovery and prototyping through production deployment and iteration
-
Build agentic AI systems — design and implement autonomous and semi-autonomous workflows using LLMs, tool-use, memory, and orchestration
-
Develop AI tools that improve efficiency across clinical operations, data extraction, manual workflows, and more
-
Commercialize AI research — partner with the AI lab to take proprietary models from research prototypes and into production
-
Contribute to model training and post-training — fine-tuning, evaluation, safety testing, and optimization of Natera's proprietary oncology models
What We're Looking For
Required
-
5+ years of software engineering experience, with at least 2 years focused on AI/ML or LLM-powered products in production
-
Demonstrated ability to ship end-to-end — you've taken AI features or products from idea to production, ideally in a zero-to-one context
-
Strong full-stack engineering skills — proficiency in Python and modern web frameworks; you can build both the model pipeline and the user-facing product
-
Production experience with LLMs — fine-tuning, RAG, prompt engineering, agentic architectures, structured extraction, evaluation, and observability
-
High agency and autonomy — you don't wait for permission, detailed specs, or hand-holding. You unblock yourself, seek out the highest-impact work, and drive it to completion
-
Excellent communication — you can translate complex AI concepts for clinical and business stakeholders, and articulate a vision for what you're building and why
Preferred
-
Experience in healthcare, biotech, diagnostics, or pharma — especially oncology
-
Familiarity with clinical workflows, electronic health records, or provider-facing software
-
Track record of working in regulated environments (HIPAA, FDA, CLIA, CAP)
-
Background in or comfort with computational biology, genomics, or multimodal data (imaging, sequencing, clinical records)
-
Experience with AWS infrastructure, Kubernetes, MLflow, or similar ML platform tooling
-
Prior experience in a high-growth startup or zero-to-one product environment