Sr. AI/ML Engineer- Digital and Consumer - Remote

UnitedHealth Group•Eden Prairie, MN

5d•$120,100 - $214,500•Remote

About The Position

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. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

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
Proven ability to design AI workflows that are explainable, testable, governable, and safe
Solid understanding of model limitations, hallucination risks, bias/fairness concerns, and responsible AI frameworks

Nice To Haves

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
Proven experience scaling LLM applications and data science solutions within large enterprise environments

Responsibilities

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