Sr AI/ML Engineer - Remote
About The Position
UnitedHealthcare is seeking a Sr AI/ML Engineer to join its LMIS team in support of UnitedHealthcare Employer & Individual modernization and the underwriting team. The role designs, builds, and optimizes AI and machine learning solutions that improve underwriting workflows, simplify health benefits planning, and modernize legacy systems. The engineer will work with Python, high-performance web APIs, large language models (LLMs), retrieval-augmented generation (RAG) pipelines, Model Context Protocol (MCP), and agent-to-agent communication protocols. The work includes automating underwriting processes, streamlining benefit assessments, and deploying production-ready AI models and agentic AI capabilities. This position can be performed remotely from anywhere in the United States. 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.
Requirements
- At least 5 years of software engineering, system integration, or machine learning engineering experience.
- At least 3 years of professional experience developing and deploying production web APIs, such as FastAPI, Flask, or RESTful services.
- At least 3 years of Python programming experience, including standard machine learning libraries such as NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow.
- At least 1 year of hands-on experience integrating or working with LLMs or generative AI concepts.
- Experience designing or implementing RAG pipelines, including embeddings, vector databases, semantic search, and LLM orchestration.
- Valid driver’s license and access to reliable transportation.
Nice To Haves
- 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 using 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 or clients, and secure agent-to-agent communication design patterns.
- Familiarity with MLOps frameworks, model performance monitoring, and model registries.
- Experience with cloud platforms such as Azure, AWS, or 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, including the ability to explain technical concepts to technical and non-technical stakeholders.
Responsibilities
- Design, develop, and deploy AI-powered solutions and platforms for complex business challenges, emphasizing responsible AI use.
- Design and implement RAG pipelines integrating enterprise knowledge sources, vector search, embeddings, and LLM orchestration patterns.
- Support agentic AI architectures by integrating MCP capabilities and agent-to-agent communication protocols for secure, interoperable workflow execution.
- Use enterprise-approved AI tools to streamline workflows and automate repetitive engineering tasks.
- Evaluate emerging AI/ML trends and approved tools to inform solution design, architectural decisions, and underwriting and modernization initiatives.
- Design, develop, and optimize Python-based AI/ML capabilities for underwriting and benefit determination needs.
- Build, integrate, and maintain high-performance, secure API endpoints that expose machine learning models and LLM functionality to core underwriting systems.
- Integrate LLMs and advanced AI model architectures into production environments to improve user workflows, benefit assessments, and operational efficiency.
- Collaborate with software engineers, data engineers, and underwriting stakeholders to deliver scalable machine learning pipelines and microservices.
- Test, monitor, and debug deployed models to support high availability, security, and performance.
Benefits
- Comprehensive benefits package, subject to eligibility requirements.
- Incentive and recognition programs.
- Equity stock purchase program.
- 401(k) contribution, subject to eligibility requirements.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
