Join Optum, a global leader in health optimization, and contribute to improving healthcare outcomes through cutting-edge AI and ML technologies. This role is pivotal in shaping the future of our AI platform, impacting millions worldwide.

As a Principal AI/ML Engineer, you will drive innovation in a dynamic environment that fosters inclusion, collaboration, and continuous growth. We are committed to empowering individuals to live healthier lives and ensuring the health system works better for everyone, addressing health disparities and promoting equitable care.

Design, develop, and maintain robust AI platform services, from concept to production.

Key responsibilities include architecting public APIs and SDKs, building the Capability Gateway with secure, typed contracts, and operating the agent harness and runtime for seamless orchestration.

Establish engineering best practices, including coding standards, CI/CD pipelines, and automated testing. Engineer the platform for cost-efficiency and scalability, focusing on inference routing, caching, and resource pooling.

Implement AI/ML capabilities in areas like NLP, semantic search, and computer vision, specifically for healthcare workflows. Develop evaluation infrastructure and leverage large-scale computing frameworks for data foundation and feature stores.

We seek a seasoned professional with a Bachelor's degree in Computer Science or a related technical field, or equivalent experience.

Requires over 10 years of experience in software engineering, with at least 5 years dedicated to designing distributed services and platform APIs. Proficiency in Python and another production language (Java, TypeScript, Scala, C++) is essential.

Demonstrated expertise in LLM-based systems, including RAG, tool calling, and orchestration, is crucial. Experience with cloud-native delivery, containers, Kubernetes, CI/CD, and distributed data processing frameworks like Spark or Databricks is required.

Candidates must possess a strong understanding of software engineering fundamentals, debugging complex production issues, performance profiling, and explaining technical concepts to diverse audiences. Experience building software under regulatory constraints is also a must.