Product & Enablement Leader, AI Productivity Tools - Remote

UnitedHealth Group•Eden Prairie, MN

2d•$134,600 - $230,800•Remote

About The Position

This senior enterprise product leadership role shapes, scales, and operationalizes the company’s AI productivity tools portfolio, including Microsoft Copilot, ChatGPT Enterprise, and Claude Enterprise. Operating at the intersection of enterprise transformation, product strategy, enablement, and value realization, this leader owns the end-to-end approach for how generative AI productivity tools are introduced, governed, adopted, measured, and continuously improved across the enterprise. The role is accountable not just for tool availability, but for making AI productivity repeatable and valuable in day-to-day work—moving the organization from early experimentation to sustained, measurable impact at scale. Success is defined by employees selecting the right tools for their work, understanding core capabilities, and applying them to deliver measurable productivity and business value. The ideal candidate is a decisive, enterprise-minded product leader with strong executive presence, deep curiosity, and a bias for action. They are comfortable operating in ambiguity, influencing without authority, and owning outcomes in a fast-moving, highly visible space. 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.

Requirements

3+ years of experience in enterprise product management, platform leadership, or digital transformation
1+ years of experience delivering AI-powered or user-facing technology products (e.g., applied AI, intelligent agents, IT automation) in production environments
Demonstrated experience leading enterprise-scale productivity or enablement platforms, preferably spanning multiple tools or vendors
Vendor management experience, including licensing, roadmap engagement, and operational readiness
Solid understanding of generative AI concepts, productivity patterns, and responsible AI considerations
Solid understanding of enterprise technology ecosystems, including cloud platforms, APIs, architecture patterns, and modern digital experience platforms
Proven ability to operate across strategy, execution, and influence, including senior executive engagement
Proven high AI acumen across the enterprise productivity tool suite, with a current understanding of capabilities, limitations, and roadmaps to guide strategy, adoption, and value realization
Demonstrated fluency using enterprise-approved AI tools in daily product management work to drive insight, efficiency, and decision-making
Proven excellent stakeholder management skills, with the ability to align business, technology, and delivery teams around a shared vision and influence without authority
Proven solid analytical and decision-making skills, with a focus on metrics, outcomes, and continuous improvement

Nice To Haves

Experience launching or scaling Microsoft Copilot, ChatGPT Enterprise, Claude, or similar AI tools in a large enterprise
Experience working in highly regulated or complex enterprise environments
Familiarity with enterprise financial models (chargeback, cost attribution, licensing strategies)
Proven background in change management, enablement, training, or workforce transformation
Proven ability to build, lead, and mature global product teams
Proven solid executive presence, with a track record of partnering with senior leaders to align priorities, manage risk, and drive measurable outcomes
Proven financial acumen, including building cost-benefit analyses and business cases to support product decisions

Responsibilities

Own the enterprise AI productivity tools portfolio strategy (Microsoft Copilot, ChatGPT Enterprise, Claude Enterprise), including positioning, differentiation, and recommended usage patterns by role and function
Define the long-term vision, near-term roadmap, and success measures for AI productivity tools as part of the broader employee experience and AI transformation agenda
Balance innovation and experimentation with enterprise requirements for security, compliance, cost transparency, and responsible AI use
Lead and develop a global product team (product and enablement owners), building a high-performing, AI-fluent organization focused on measurable adoption and business value
Define and manage value-realization measures and communicate outcomes through concise, executive-ready storytelling
Partner with executive leadership to align AI productivity tools to enterprise priorities, transformation goals, and workforce impact
Proactively identify gaps, opportunities, and risks, and drive decisions that move from strategy to execution
Stay current on the AI landscape—tracking vendor announcements, emerging capabilities, and industry trends to inform strategy, roadmap decisions, and adoption plans
Shape the workforce AI skills strategy—ensuring employees not only adopt tools, but build lasting capability and confidence in applying AI to real work
Design and lead a multi-layered enablement strategy that includes self-service learning, targeted training, hands-on experiences, communities of practice, and in-the-flow-of-work guidance
Partner with stakeholders and executives to evangelize AI productivity tools through practical, role-based stories and examples
Ensure enablement is outcome-oriented—moving beyond tool training to sustained behavior change and productivity gains
Own prioritization and decision-making for the AI productivity tools portfolio, balancing innovation, risk, cost, and value realization
Partner with product operations to define and maintain the operating model for AI productivity tools, including intake, access models, support patterns, escalation paths, and lifecycle management
Coordinate across platform, security, finance, legal, and support teams to ensure smooth onboarding, clear guardrails, and scalable operations
Use real-world feedback to continuously refine governance and reduce friction while maintaining enterprise standards
Establish clear adoption, usage, and value metrics for AI productivity tools aligned to enterprise transformation goals
Synthesize qualitative and quantitative insights to inform roadmap decisions, executive updates, and investment prioritization
Translate signals from support, training, and usage data into actionable improvements across products, enablement, and policy
Act as a connector across product, engineering, platform, enablement, and business stakeholders, enabling shared accountability for AI productivity outcomes
Influence senior leaders by framing AI productivity in terms of measurable business outcomes, not tools or features
Own strategic vendor relationships across the AI productivity portfolio, influencing roadmaps, feature prioritization, and enterprise readiness so tools evolve in line with organizational needs and value objectives