Note: The job is a remote job and is open to candidates in USA. UnitedHealthcare is simplifying the health care experience, creating healthier communities, and removing barriers to quality care. The Senior AI/ML Engineer will design, develop, and deploy AI and machine learning solutions for underwriting workflows, benefits planning, and health care modernization. The role focuses on RAG pipelines, LLMs, agentic AI, Python-based machine learning capabilities, secure APIs, and production model operations.
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
Skills
- • 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
- • 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
- • All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
Benefits
- Flexibility to work remotely from anywhere within the U.S.
- A comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401k contribution
- Development for other roles you may be interested in
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