Director, AI Data Strategy and Enablement - Remote

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.

United Health Group is building an enterprise-scale AI operating model. AI experiences require trusted, connected, contextual, interpretable, governed, and actionable data that AI systems can discover, reason over, and use appropriately across journeys and workflows. In a complex health care enterprise, this data is distributed across products, platforms, business units, legacy systems, documents, operational processes, and external partners.

As Director, AI Data Strategy & Enablement, you will define and lead the strategy for how enterprise data, context, and capabilities enable next-generation digital and AI experiences for our 50+ million members. You will establish the vision, operating model, priorities, standards, and roadmap required to make enterprise data AI-ready and agent-ready.

This is a highly strategic, cross-functional leadership role. You will work across Digital, Product, Technology, Data & Analytics, AI, Architecture, Operations, Compliance, Risk, and business teams to identify high-value opportunities, lead structured discovery, define future-state capabilities, and mobilize a highly matrixed organization around a common strategy.

You will bring design thinking, systems thinking, structured discovery, and data strategy to ambiguous enterprise problems, translating business and experience needs into actionable data and capability strategies. You will also shape how data and context are made usable by AI agents and digital skills, including discoverability, semantics, retrieval, permissions, interoperability, governance, and observability.

You will help move the organization from fragmented sources of information toward a trusted, reusable, semantic, interoperable data ecosystem that enables personalized digital experiences and scales AI safely across the enterprise.

You'll enjoy the flexibility to work remotely
* from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

• Define Enterprise AI Data Strategy & Roadmap
  • Define the vision, principles, strategic priorities, and multi-year roadmap for AI-ready and agent-ready data aligned to enterprise AI and digital experience priorities
  • Identify the data, semantic, knowledge, context, access, interoperability, governance, and observability capabilities required to scale AI
  • Prioritize investments based on member and business value, feasibility, reuse potential, and strategic importance
  • Balance near-term AI use cases with foundational capabilities that enable long-term scale and reduce fragmented or duplicative investments
  • Establish the operating model, decision rights, and partnerships needed to execute the strategy across the enterprise
• Lead Discovery, Experience Strategy & Enterprise Alignment
  • Lead structured discovery with product, business, clinical, operations, technology, data, and experience stakeholders to understand needs, outcomes, constraints, and root causes
  • Apply design thinking, journey-based discovery, systems thinking, and hypothesis-driven problem solving to identify opportunities for AI-enabled experiences
  • Translate ambiguous problems into clear strategic choices, capability requirements, and actionable roadmaps
  • Facilitate alignment across stakeholders with competing priorities, different definitions, or conflicting perspectives on data and technology
  • Build executive alignment and influence decisions across a complex, highly matrixed organization without direct authority
• Shape the Data Foundation for Agentic AI
  • Define principles and requirements for agent-ready data, including trust, freshness, lineage, semantics, discoverability, permissions, interoperability, and machine usability
  • Shape the role of semantic models, metadata, ontologies, knowledge, data products, retrieval, and context layers in AI experiences
  • Partner with Architecture, Technology, Engineering, and Data leaders to establish scalable patterns for AI access to enterprise data and systems, including APIs, tools, retrieval services, and other governed access mechanisms
  • Ensure AI experiences are grounded in authoritative enterprise sources and business context and can operate within appropriate policy, risk, and human-escalation controls
  • Establish requirements for data provenance, observability, traceability, auditability, and responsible use as AI…