Senior AI/ML Engineer

UnitedHealth Group•Minnetonka, MN

5h•$120,100 - $214,500•Remote

About The Position

Optum Tech is adding resources to its Claim Edit Hub team to support AI 10.0 scaling. The team will derive claim rules and edits directly from source documents, such as policies, and expose them through agentic workflows for real-time access. The work will also support a “shift left” strategy that enables claim edits and rules to run on trial claims, providing transparent cost estimates to providers and members. The Senior AI/ML Engineer designs, develops, and deploys scalable AI/ML models and automation solutions, and builds and maintains end-to-end machine-learning pipelines. The role develops MLOps automation frameworks and integrates AI/ML solutions into production systems using CI/CD and cloud platforms. The engineer collaborates across data science, engineering, product, and business teams, and is responsible for model performance, scalability, reliability, governance, compliance, and data integrity. The position can be performed remotely from anywhere in the U.S. Employees hired in the Minneapolis or Washington, D.C. area must work in the office at least four days per week. Remote employees must follow UnitedHealth Group’s Telecommuter Policy. The role offers a salary range of $120,100–$214,500 annually based on full-time employment, along with benefits subject to eligibility requirements.

Requirements

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 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.

Nice To Haves

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.
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.

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 AI models are scalable, reliable, and governed, including compliance and data integrity.
Integrate AI/ML solutions into production systems using CI/CD and cloud platforms.
Stay current with emerging AI/ML technologies and automation best practices to drive innovation.