Senior Product Manager - AI Transformation, UMR - Remote

UnitedHealth Group is simplifying the health care experience and creating healthier communities. They are seeking a Senior Product Manager - AI Transformation to lead business analysis and delivery governance for AI solutions within UMR Operations, focusing on improving claims operations and ensuring regulatory compliance.

Responsibilities:

• Lead business analysis strategy and governance across a multi-product Agentic AI portfolio supporting claims operations (First Pass Adjudication, High Dollar Claims, Payment Integrity, Rework Automation, Reverse Quality Engine)
• Establish and standardize requirements frameworks, documentation standards, traceability models, and acceptance criteria across all AI initiatives
• Align AI solution design with business objectives by collaborating with Product, IT Architecture, Data Science, Clinical, Pricing, Network, Compliance, and Payment Integrity stakeholders
• Oversee translation of complex claims processing logic into AI-driven rules, prompts, and decision frameworks ensuring regulatory and contractual compliance
• Manage cross-workstream dependencies, integration points, and delivery sequencing across multiple AI initiatives
• Implement governance for AI rule libraries, prompt frameworks, and reusable decision components to ensure consistency and scalability across products
• Partner with a team of capability manager responsible for detailed requirements elaboration and product delivery support
• Lead through influence to drive portfolio-level consistency and reuse of operational rules and AI decision patterns to accelerate implementation and reduce redundant build efforts
• Partner with program leadership to track value realization including improvements in cycle time, auto-adjudication rate, payment accuracy, and rework reduction
• Support stakeholder governance, executive reporting, and operational alignment across business and technology teams
• Ensure audit readiness, compliance traceability, and documentation for AI-enabled decision processes in claims operations

Requirements:

• 8+ years of experience in healthcare payer operations, healthcare consulting, or healthcare technology delivery
• 5+ years of experience in healthcare claims operations including adjudication, payment integrity, or benefits administration
• 3+ years of experience leading business analysis teams or complex transformation initiatives
• Experience leading cross-functional initiatives involving product, IT, operations, and compliance teams
• Experience in creating structured strategies and solution artifacts (e.g., use case briefs, process flows) and integrating models into existing products/capabilities
• Experience in PDLC and AIDLC while leveraging modern product management tools - Aha!, JIRA, FIGMA, MIRO, GitHub, etc
• Demonstrated experience managing enterprise-level requirements strategy and governance
• Demonstrated experience defining or contributing to AI use case strategy, including problem framing, value hypotheses, and measurable success metrics
• Deep understanding of healthcare claims processing including eligibility and benefits, coding edits, modifiers, coordination of benefits (COB), authorization rules, bundling/unbundling, contract pricing, and adjustments
• Demonstrated solid stakeholder management and executive communication skills
• Proven ability to design or operate within AI intake and prioritization frameworks, including evaluating initiatives based on business impact, feasibility, and adoption potential
• Experience implementing AI, automation, or decision intelligence solutions within healthcare payer operations
• Experience with payment integrity programs, claims editing platforms, or healthcare pricing systems
• Experience evaluating and supporting legal, compliance, and risk considerations for AI solutions, including areas such as model governance, responsible AI, and regulatory alignment
• Experience working with large payer organizations or third-party administrators
• Knowledge of Agentic AI frameworks, prompt design, or rule-based automation in operational workflows
• Working knowledge of production AI systems, including MLOps or deployment considerations
• Familiarity with Agile or product-based delivery models in enterprise technology environments