Lead AI Technical Product Manager

UnitedHealth Group•Eden Prairie, MN

1d•$112,700 - $193,200

About The Position

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 AI Technical Product Manager to join our Optum Tech UHC Technology team within the UHC Operations and Experience division. In this role, you will own AI product strategy end-to-end - defining the vision, roadmap, and long-term strategy while aligning technology delivery with business priorities. Acting as the critical bridge between business outcomes, data readiness, model capabilities, and engineering execution, you will move beyond research and prototyping to deliver and maintain applied AI systems in production. You will design and scale modern, high-quality technical platforms that leverage data, automation, and AI/ML - including generative AI (GenAI), agentic AI, and autonomous AI agents - to improve operational efficiency and business outcomes. Partnering closely with engineering, data science, and design teams, you will champion Agile execution, full model lifecycle ownership, and the responsible use of AI to build scalable, secure systems that drive measurable business impact.

Requirements

Bachelor’s degree in Engineering, Computer Science, Business, or a related field, OR equivalent experience (4+ years of additional product management or technology delivery experience in lieu of a degree)
10+ years of experience in technical product management, technology delivery, or data platform management
5+ years of experience leading complex, enterprise-scale technology products from concept to implementation (vision to production)
3+ years of experience writing business requirements and technical product specifications within an Agile development methodology
2+ years of experience working directly with cloud technologies (e.g., Snowflake, Azure, AWS) and data/analytics architectures
2+ years of experience delivering or managing AI-enabled or Applied AI products in production (real-world delivery, not just research or prototyping)

Nice To Haves

Master’s degree in Engineering, Computer Science, Business, or a related field
3+ years of experience delivering and managing Applied AI or Production AI systems, including generative AI or agentic AI solutions, in real-world environments
Hands-on experience delivering generative AI or agentic AI solutions in production (e.g., LLM applications, AI agents, multi-agent systems, RAG pipelines, or agent orchestration frameworks)
Experience defining and driving product roadmaps and strategic visions for data-driven, automated, or AI/ML-powered systems
Experience with model lifecycle ownership, including monitoring and performance tuning in production environments
Experience managing data governance, privacy compliance, and security policies within an enterprise environment
Working fluency in AI/ML concepts - including an understanding of model capabilities, limitations, outcomes, and data requirements (non-hands-on modeling) - with a working understanding of generative AI and agentic AI concepts such as large language models (LLMs), AI agents, prompt engineering, and orchestration/RAG patterns
Technical working knowledge of APIs, cloud platforms (primarily Azure), and the Software Development Life Cycle (SDLC)
Proven ability to influence senior stakeholders and align cross-functional, geographically distributed teams within a complex, matrixed global organization
Proven excellent problem-solving, risk mitigation, and decision-making skills with a high ownership mindset
Proven solid communication skills with a proven ability to translate complex technical and AI concepts into business-friendly language for executive audiences

Responsibilities

Own the end-to-end AI product strategy - vision, roadmap, prioritization, and long-term strategy aligned with business priorities; translate business goals into clear product objectives, success metrics, and quantifiable KPIs
Design, develop, and deploy AI-powered, automation-driven, and data platform solutions to complex business challenges, translating AI/ML capabilities into clear value propositions for users and business leaders
Drive the adoption and productization of generative AI (GenAI), agentic AI, and AI agent solutions - including LLM-powered applications, multi-agent orchestration, retrieval-augmented generation (RAG), and autonomous or semi-autonomous workflows - while defining the guardrails, evaluation criteria, and human-in-the-loop controls needed for safe, reliable operation
Be accountable for the performance and reliability of AI systems in production - moving beyond research and prototypes to scalable, real-world applications - and manage the complete model lifecycle so solutions are continuously monitored, evaluated, and improved based on production feedback
Leverage and advocate for enterprise-approved AI tools and modern technologies (cloud, automation, AI/ML) to streamline workflows, automate tasks, and drive continuous improvement across operations
Own the end-to-end product lifecycle from ideation through development, launch, and optimization. Prioritize the product backlog, define features, write specifications, and drive Agile ceremonies (planning, grooming, reviews)
Lead cross-functional teams across engineering, data science, design, and business stakeholders to deliver high-quality, scalable, and secure solutions, evaluating technical architectures and cloud approaches
Act as the primary interface between business stakeholders, leadership, and technical teams; communicate product strategy, progress, risks, and outcomes clearly to executive leaders
Lead the development of data platforms, reporting solutions, and integrated data pipelines while defining data requirements, governance standards, and integration approaches to ensure data readiness for AI
Champion the ethical use of AI by embedding transparency, fairness, and accountability throughout the AI lifecycle; identify and manage risks - including incorrect predictions, unintended bias, and downstream business impact - while ensuring strict compliance with enterprise data privacy and security policies
Gather and synthesize user feedback to refine product offerings, tracking performance metrics to ensure solutions drive measurable business value (efficiency, cost savings, and quality improvement)
Maintain a minimum of 90%25 weekly usage of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other GenAI platforms approved by the enterprise
Leverage AI tools to enhance coding, documentation, data analysis, and decision-making workflows
Stay current with evolving AI capabilities and features, and apply them to improve delivery quality and velocity