Head of AI/ML Engineering

The Head of AI Engineering is a technology and entrepreneurial Generative AI engineering leader who will build and scale our new Generative AI and ML Solutions team. You will be responsible for building and executing our Generative AI engineering strategy, governance, and delivery across the organization while aligning them with the organization’s strategic goals of using AI to improve productivity, efficiency, and experience. In this role, you will be at the forefront of the generative AI change, leading a world-class engineering organization that designs and implements cutting-edge solutions to solve Natera’s AI/ML challenges. As part of this role, you will join Natera’s AI office as a key executive member and will be accountable for building and executing an AI solutions delivery plan in alignment with business needs to unlock transformative business value

• Own the end-to-end technical vision for the entire AI/ML platform, from data ingestion, MLOps, model serving, fine-tuning, foundation model training, RAG, and agentic applications. 

• Make the critical "build vs. buy vs. open-source" decisions that balance speed, cost, and long-term defensibility

• Recruit, hire, mentor, and retain an elite team of T shaped AI engineers, applied ML engineers, data scientists, and platform engineers. 

• Design a rigorous hiring process to find "unicorn" talent and foster a culture of continuous learning and excellence.

• Design, build, and scale an AI/ML platform that provides standardized tooling, infrastructure, and workflows for LLM training, fine-tuning, retrieval-augmented generation (RAG), AI orchestration, and deployment.

• Develop reusable components and services (e.g., vector databases, prompt libraries, agent frameworks, model registries, evaluation pipelines, safety/guardrail modules) to accelerate delivery of AI solutions across product engineering teams.

• Ensure reliability, scalability, and compliance of the AI/ML platform by implementing robust observability, governance, and cost-optimization strategies tailored for large model serving and API consumption.

• Partner with business and product owners to identify, design, and implement high-impact AI solutions that drive measurable outcomes, ensuring alignment with strategic priorities.

• Own the full lifecycle of AI solutions — from prototyping and deployment through ongoing monitoring, maintenance, and enhancements — ensuring solutions remain accurate, performant, and relevant as business needs evolve.

• Continuously improve deployed AI systems by incorporating feedback, retraining models, and updating components to adapt to changing data, regulatory requirements, and operational realities.

Operational Excellence

• Implement robust processes for quality assurance, model governance, and performance monitoring.

• Drive adoption of a combination of hyper-scaler AI services and specialized cloud native AI solutions to accelerate time-to-market.

• Lead cost observability and management initiatives to optimize AI infrastructure and usage at scale.

• Ensure compliance with AI Governance policies

• Serve as the primary bridge between business stakeholders and the AI Office.

• Ensure AI product roadmaps align with Natera’s broader AI vision and business objectives.

• Champion a culture of responsible AI adoption, ensuring ethical, compliant, and explainable use of AI.

• Translate business needs into actionable technical requirements for engineering and business teams.
  Collaborate with security, regulatory, compliance, and legal to ensure solutions meet security and regulatory standards.

• Partner with AI Governance and Change Enablement leads to ensure trust, fairness, and adoption across the organization.

• 15+ years of experience in an engineering leadership role in AI, ML, or data science

• Expertise in Generative AI, including LLMs, prompt engineering, RAG, fine-tuning, training, and evaluation methodologies.

• Proven track record of delivering production-grade AI solutions in customer-facing and internal products especially using LLMs and ML models

• Strong understanding of production software engineering best practices, CI/CD, testing, observability, error handling, and security.

• Experience with AWS based AI services and other specialized AI platforms (e.g., AWS Bedrock, Snowflake AI, Google AI, OpenAI, xAI).

• Demonstrated ability to optimize AI model performance and costs for large-scale deployments especially LLMs.

• Exceptional communication and cross-functional collaboration skills.

• Excellent stakeholder engagement, prioritization, and communication skills.

• Advanced degree (MS/PhD) in Computer Science, AI/ML, engineering or related field.

• Experience in healthcare, pharma, diagnostics, or other regulated industries.

• Familiarity with AI governance frameworks, bias detection, explainability, and compliance (e.g., HIPAA, CLIA, FDA).