Sr. AI​/ML Engineer - Remote or Hybrid in Eden Prairie, MN or Irvine, CA

Improve the lives of others while Caring. Connecting. Growing together.

Job Description
- Sr. AI/ML Engineer
- Remote or Hybrid in Eden Prairie, MN or Irvine, CA (2380618)

Sr. AI/ML Engineer
- Remote or Hybrid in Eden Prairie, MN or Irvine, CA - 2380618

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities.

Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

The Chief Digital Office Consumer Engineering team is seeking a Senior AI/ML Engineer to own and advance the intelligence layer of our consumer-facing solutions. In this role, you will design, build, evaluate, and continuously improve AI components, including LLM workflows, RAG pipelines, agentic behaviors, classifiers, summarizers, copilots, and AI evaluation frameworks. Our team's mission is to create innovative digital capabilities that directly impact millions of consumers while ensuring that every AI solution is useful, measurable, safe, transparent, and fit for enterprise execution.

If you are located in Eden Prairie, MN or Irvine, CA, you will have the flexibility to work remotely*, as well as work in the office as you take on some tough challenges.

• Design, develop, and deploy AI-powered solutions, LLM workflows, prompt chains, agents, RAG patterns, model integrations, classification models, and decision-support tools to address complex business challenges
• Develop prompt strategies, tool-calling patterns, grounding techniques, guardrails, and fallback behaviors with an emphasis on responsible AI practices
• Partner with Data Engineering to ensure AI components have access to trusted, appropriate, and governed data sources
• Build and maintain evaluation datasets, scoring rubrics, model-performance tests, and failure-mode analysis tools
• Monitor and continuously improve output quality, hallucination risk, relevance, accuracy, consistency, latency, and operational cost in production environments
• Partner with Quality Assurance, Responsible AI, Security, Privacy, Compliance, and Architecture teams to ensure AI solutions are safe and enterprise-ready
• Document model behavior, known limitations, risk controls, and operational monitoring needs, while supporting production readiness, model observability, and drift monitoring
• Evaluate emerging trends and leverage enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous strategic innovation

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

• 5+ years of engineering experience with strong technical proficiency in Python or equivalent programming language
• Practical experience building and deploying AI-enabled applications in enterprise settings, including hands‑on experience with LLMs, RAG, embeddings, vector search, prompt engineering, and agent frameworks
• Demonstrated experience working with model APIs, orchestration frameworks, data pipelines, and evaluation tooling
• Solid understanding of model limitations, hallucination risks, bias/fairness concerns, and responsible AI frameworks
• Proven ability to design AI workflows that are explainable, testable, governable, and safe

• Bachelor’s or Master’s degree in Data Science, Computer Science, Machine Learning, or related technical discipline
• Solid background in Data Science, Machine Learning Engineering, Applied Science, or Full-Stack Engineering with AI specialization
• Practical experience with statistical modeling, data analysis, controlled testing, model evaluation frameworks, and production AI monitoring tools
• Prov…