Sr. AI Engineer - Remote or Hybrid in Eden Prairie, MN

About the role

We are seeking a Sr AI/ML Engineer to join our LMIS team in supporting UnitedHealthcare Employer & Individual (E&I) modernization and our underwriting team. In this role, you will design, build, and optimize cutting-edge AI and machine learning solutions that directly improve underwriting workflows, simplify the healthcare benefits planning experience, and modernize core legacy systems. You will work within a collaborative environment leveraging a modern technology stack, including Python, high-performance web APIs, Large Language Models (LLMs), retrieval-augmented generation (RAG) pipelines, Model Context Protocol (MCP), and agent-to-agent communication protocols. Your work will be highly impactful, helping to automate complex underwriting processes, streamline benefit assessments, and deploy production-ready AI models and agentic AI capabilities to enhance operational efficiency.

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 AI-powered solutions and platforms to address complex business challenges with a solid emphasis on the responsible use of AI
• Design and implement retrieval-augmented generation (RAG) pipelines that integrate enterprise knowledge sources, vector search, embeddings, and LLM orchestration patterns
• Support agentic AI architectures by integrating Model Context Protocol (MCP) capabilities and agent-to-agent communication protocols for secure, interoperable workflow execution
• Leverage enterprise-approved AI tools to enhance productivity and innovation by streamlining workflows and automating repetitive engineering tasks
• Evaluate emerging trends and approved toolsets in the AI/ML landscape to inform solution design, architectural decisions, and strategic underwriting and modernization initiatives
• Design, develop, and optimize robust AI/ML capabilities using Python to address complex underwriting and benefit determination business needs
• Build, integrate, and maintain high-performance, secure API endpoints to expose machine learning models and LLM functionalities to core underwriting systems
• Integrate Large Language Models (LLMs) and advanced AI model architectures into production environments to enhance user workflows, benefit assessments, and operational efficiency
• Collaborate with software engineers, data engineers, and underwriting stakeholders to deliver scalable machine learning pipelines and microservices
• Ensure high availability, security, and performance of deployed models through rigorous testing, monitoring, and debugging

Required Qualifications

• 5+ years of software engineering, system integration, or machine learning engineering experience
• 3+ years of professional experience developing and deploying robust web APIs (such as FastAPI, Flask, or RESTful services) in production environments
• 3+ years of experience programming in Python, including standard machine learning libraries (such as NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow)
• 1+ years of hands-on experience integrating or working with Large Language Models (LLMs) or generative AI concepts
• Experience designing or implementing retrieval-augmented generation (RAG) pipelines, including embeddings, vector databases, semantic search, and LLM orchestration
• Driver's License and access to reliable transportation

Preferred Qualifications

• Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field (or equivalent years of experience)
• Experience in health insurance, financial services, or supporting underwriting systems and technologies
• Experience utilizing generative AI development tools (such as LangChain, Hugging Face, or prompt engineering frameworks) to build application solutions
• Experience with vector databases, knowledge retrieval patterns, prompt grounding, tool calling, or enterprise search integration
• Familiarity with agent orchestration frameworks, multi-agent systems, MCP servers/clients, and secure agent-to-agent communication design patterns
• Familiarity with MLOps frameworks, model performance monitoring, and model registries
• Experience with cloud platform environments (e.g., Azure, AWS, GCP) and containerization tools (such as Docker or Kubernetes)
• Familiarity with CI/CD deployment pipelines and git-based source control workflows
• Excellent communication and collaboration skills with the ability to articulate technical concepts to both technical and non-technical stakeholders

Pay

The salary for this role will range from $120,100 to $214,500 annually based on full-time employment.