Senior AI/ML Engineer

Join Optum Tech

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us in making healthcare work better for everyone through people-led, responsible AI while Caring. Connecting. Growing together.

In support of AI 10.0 Scaling and leveraging AI to apply processing rules directly from source documentation via enterprise assets, we're adding resources to our Claim Edit Hub team. This team will work to derive rules/edits directly from source documents (i.e. Policies) and expose them via Agentic workflow to make them accessible in a real time manner. This will also support our'shift left' strategy to enable claim edits/rules to be executed on Trial Claims to provide transparent cost estimates to Providers and Members.

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.

Primary Responsibilities

• Design, develop, and deploy scalable AI/ML models and automation solutions to solve complex business problems
• Build and maintain end-to-end ML pipelines including data ingestion, feature engineering, model training, and deployment
• Develop automation frameworks for model training, testing, validation, and monitoring (MLOps)
• Collaborate with data science, engineering, product, and business teams to deliver AI-driven solutions
• Optimize model performance through continuous evaluation, tuning, and retraining strategies
• Ensure scalability, reliability, and governance of AI models including compliance and data integrity
• Integrate AI/ML solutions into production systems using CI/CD and cloud platforms
• Stay updated with emerging AI/ML technologies and automation best practices to drive 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.

Required Qualifications

• Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical field
• 5+ years of software engineering, AI engineering, or machine learning engineering experience
• 3+ years of hands-on experience developing AI/ML solutions, including Generative AI, LLMs, NLP, and traditional machine learning models
• 3+ years of experience designing, building, and deploying production-grade LLM applications, RAG pipelines, AI agents, and orchestration workflows
• 5+ years of solid Python development experience supporting AI and data-intensive applications
• 3+ years of experience with AWS AI and cloud-native services including Bedrock, SageMaker, Lambda, OpenSearch, ECS/EKS, and S3
• 2+ years of experience with vector databases, embeddings, semantic search, and enterprise knowledge retrieval systems
• 2+ years of experience implementing MLOps, LLMOps, model monitoring, evaluation frameworks, and AI operationalization practices

Preferred Qualifications

• 2+ years of hands-on experience with Agentic AI frameworks such as LangGraph, Semantic Kernel, CrewAI, AutoGen, MCP, or AgentCore
• Experience implementing multi-agent architectures and autonomous workflow orchestration
• Experience with AI evaluation frameworks, hallucination reduction techniques, model benchmarking, and prompt optimization
• Demonstrated familiarity with Knowledge Graphs, Ontologies, GraphRAG, and enterprise knowledge systems.
• Experience building reusable AI platform services supporting multiple use cases
• Experience implementing Retrieval-Augmented Generation (RAG), prompt engineering, semantic search, and knowledge retrieval systems

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $120,100 - $214,500 annually based on full-time employment. We comply with all minimum wage laws as applicable.

Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

At UnitedHealth Group, our mission is to help people live healthier lives and help make the health system work better for everyone. Together, we are shaping the future of healthcare by harnessing technology and innovation to make care simpler to navigate, more affordable and more connected for the people we serve. We are committed to creating an inclusive workplace where everyone feels welcomed, valued, heard and respected, empowering people to bring their authentic selves to work and strengthening our collective impact through diverse talents, backgrounds, experiences and perspectives.

UnitedHealth Group and its affiliated brands are an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

UnitedHealth Group and its affiliated brands are a drug-free workplace. Candidates are required to pass a drug test before beginning employment.