Note: The job is a remote job and is open to candidates in USA. UnitedHealth Group is a global leader in health care innovation, seeking a Senior AI ML Engineer to design and deploy AI-powered solutions. The role focuses on building agentic AI workflows and advanced reasoning systems to optimize clinical workflows and improve health outcomes.
Responsibilities
- Design, develop, and deploy robust AI-powered solutions and agentic AI workflows to address complex clinical and business challenges, with an emphasis on the responsible and ethical use of AI
- Build and implement agentic AI systems that reason over clinical workflows, orchestrate multi-step tasks, interact with APIs and system tools, and integrate human-in-the-loop decision-making frameworks
- Develop scalable, reusable AI components using LLM orchestration frameworks, advanced prompt engineering patterns, retrieval-augmented generation (RAG), and vector databases
- Use Python as a core engineering language to write production-grade automation scripts, pipelines, backend services, and reusable integration components
- Leverage enterprise-approved AI tools and developer platforms to streamline workflows, automate repetitive tasks, and drive continuous platform improvement
- Evaluate emerging AI trends, agent patterns, and automation frameworks to inform secure solution design and drive continuous, strategic platform innovation
- Collaborate closely with product, clinical, data, architecture, security, and engineering teams to translate complex requirements into secure, compliant, and production-ready capabilities
- Support the operationalization, monitoring, observability, and MLOps/LLMOps of AI systems, ensuring compliance with healthcare data privacy, security, and regulatory guidelines
Skills
- Bachelor's degree
- 5+ years of experience in AI/ML engineering, software engineering, data engineering, or automation engineering, with hands-on experience delivering production-grade solutions
- 3+ years of experience using Python for automation, backend services, API integrations, and code deployment
- 2+ years of experience building solutions using Large Language Models (LLMs), generative AI, prompt engineering, or retrieval-augmented generation (RAG)
- 1+ years of experience developing agentic AI systems, including multi-step reasoning workflows, task orchestration, or tool-calling agents
- Hands-on experience with modern AI orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or cloud-native AI services)
- Experience deploying scalable AI solutions within cloud environments (e.g., Azure, AWS, GCP) using microservices, containers, or serverless architectures
- Master's degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or a related field
- Experience developing AI solutions specifically for healthcare domains, such as care management, clinical documentation, utilization management, or clinical applications
- Experience configuring and integrating vector databases or search platforms (e.g., Azure AI Search, Pinecone, Weaviate, FAISS, Chroma, OpenSearch, or Elasticsearch)
- Experience with traditional ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) combined with LLM-based workflows
- Experience with LLM evaluation frameworks, prompt versioning, synthetic data generation, and LLMOps monitoring tools
- Solid understanding of security design in regulated environments, including role-based access control, encryption, and safe handling of PII/PHI
Benefits
- A comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements)
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