Lead AI/ML Engineer

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

We are seeking a Lead GenAI Specialist to provide technical leadership for enterprise Generative AI and Agentic AI initiatives. This role is responsible for driving architecture decisions, defining reusable AI platforms and frameworks, guiding complex solution delivery, and accelerating adoption of GenAI capabilities across the organization.

Success will be measured through business impact, platform adoption, scalability of AI solutions, reusable enterprise capabilities, and advancement of organizational AI maturity.

Primary Responsibilities

AI Strategy and Technical Leadership
Define technical direction for enterprise Generative AI and Agentic AI initiatives
Lead architecture decisions for complex AI programs and strategic business use cases
Establish AI standards, reference architectures, governance models, and engineering best practices
Evaluate emerging foundation models, frameworks, and AI platforms to guide enterprise adoption
Mentor GenAI Specialists, engineers, and AI practitioners while leading small delivery teams
Enterprise GenAI Solution Architecture
Design scalable GenAI solutions aligned with business, security, compliance, and operational requirements
Architect multi-model solutions leveraging proprietary and open-source foundation models
Define reusable patterns for AI assistants, copilots, intelligent search, automation, and decision-support systems
Create reference implementations, accelerators, and reusable frameworks to accelerate enterprise adoption
Foundation Models and Model Engineering
Lead foundation model evaluation, benchmarking, selection, fine-tuning, and deployment strategies
Define standards for model adaptation techniques including SFT, LoRA, QLoRA, PEFT, and domain tuning
Optimize model quality, latency, throughput, scalability, and cost efficiency
Govern model lifecycle processes including evaluation, validation, release management, and production readiness
Knowledge Systems
Architect enterprise RAG solutions supporting large-scale knowledge retrieval and GenAI applications
Design retrieval frameworks including ingestion, chunking, embeddings, indexing, semantic search, reranking, and grounding
Establish enterprise patterns for vector search, hybrid retrieval, knowledge graphs, and AI-ready content platforms
Define evaluation frameworks to improve retrieval quality, groundedness, and response accuracy
Agentic AI and Intelligent Automation
Design and govern enterprise Agentic AI architectures
Build autonomous and human-in-the-loop workflows using tool integration, planning, reasoning, and orchestration frameworks
Lead development of single-agent and multi-agent systems for complex business processes
Establish standards for agent memory, context management, state handling, and agent observability
AI Platforms, LLMOps and Integration
Define architecture for enterprise AI platforms, gateways, model orchestration, and shared AI services
Drive LLMOps practices including deployment automation, monitoring, evaluation, governance, and lifecycle management
Establish secure integration patterns across applications, APIs, data platforms, and business workflows
Partner with platform and engineering teams to operationalize scalable AI capabilities
AI Quality, Governance and Responsible AI
Define enterprise standards for AI evaluation, observability, monitoring, and quality measurement
Establish controls for Responsible AI, model governance, safety, security, compliance, and risk management
Implement guardrails for hallucination mitigation, content safety, prompt security, and data protection
Drive AI cost optimization through model routing, caching, prompt engineering, and workload optimization
Organizational Impact
Lead enterprise AI innovation and capability-building initiatives
Influence AI roadmaps, platform investments, and architectural direction
Drive adoption of reusable AI frameworks, accelerators, and shared services
Promote knowledge sharing and technical excellence across teams
Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Required Qualifications

Bachelor's degree in computer science, Artificial Intelligence, Machine Learning, Engineering, Data Science, or related field
12+ years of experience in AI, Machine Learning, Software Engineering, AI Platforms, or related disciplines
5+ years of hands-on experience delivering Generative AI and LLM-based solutions in production environments
Proven experience leading complex enterprise GenAI and Agentic AI initiatives
Hands-on experience with RAG architectures, semantic retrieval, vector search, and enterprise knowledge systems
Experience building AI platforms, AI gateways, orchestration layers, and shared GenAI services
Experience implementing AI evaluation, observability, governance, and Responsible AI practices
Solid programming experience in Python and AI application development
Experience with Azure, AWS, or GCP AI platforms
Solid expertise in foundation models, transformer architectures, embeddings, tokenization, inference optimization, and context management
Solid understanding of Agentic AI frameworks, tool integration, workflow automation, and multi-agent systems
Proven excellent communication, stakeholder management, mentoring, and technical leadership skills

Preferred Qualifications

Master's degree
Advanced degree in Artificial Intelligence, Machine Learning, Computer Science, or related field
Experience leading small teams of GenAI engineers, architects, or specialists
Experience with LangChain, LangGraph, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, or similar frameworks
Experience building enterprise AI platforms, gateways, model catalogs, and reusable AI services
Experience with vector databases such as Pinecone, Weaviate, FAISS, Chroma, pgvector, Azure AI Search, and Neo4j
Experience implementing enterprise LLMOps, AI governance, AI security, and compliance frameworks
Experience building AI accelerators, shared frameworks, and enterprise AI reference architectures
Healthcare, insurance, financial services, or other regulated industry experience
Expertise with Azure OpenAI, Azure AI Foundry, Bedrock, Vertex AI, Anthropic, OpenAI, and open-source model ecosystems
Expertise in advanced RAG architectures including hybrid search, graph retrieval, reranking, and knowledge graphs
Proven contributions to patents, publications, enterprise innovation programs, or AI thought leadership initiatives

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
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