Group Director, Product Management - Last Mile Optimization & AI

Walmart Walmart · Retail · Sunnyvale, CA +2

Group Director of Product Management for Last Mile Optimization & AI at Walmart, focusing on the intelligence layer that powers critical decisions in the delivery ecosystem. The role involves setting vision and strategy for AI across pricing, matching, batching, and routing, building and scaling horizontal AI platforms, and operating/evolving a live, large-scale system. Requires strong product leadership, marketplace and optimization expertise, and partnership with data science on optimization models and ML systems.

What you'd actually do

  1. Set and drive the vision and strategy for optimization and AI across pricing, matching, batching, routing, and store-aware decisioning—incorporating real-time operational signals from stores and drivers.
  2. Build and scale horizontal AI platforms that power real-time, high-stakes decisioning across the entire ecosystem, including the underlying data foundations, consistent metrics, governance, and shared signals that ensure reliable and aligned decision-making across systems.
  3. Improve cost, reliability, and speed in an already scaled system—balancing short-term performance with long-term architectural evolution, while accounting for real-world variability in store operations.
  4. Work closely with Engineering and Data Science to deliver scalable, explainable, and continuously improving optimization and ML systems in production environments.
  5. Optimize a complex, multi-sided ecosystem across customers, drivers, and store operations—balancing driver earnings, cost efficiency, and service reliability.

Skills

Required

  • 12+ years in product management
  • leading leaders and scaling large, high-impact teams
  • building or operating systems with tight coupling between supply, demand, and operational constraints (e.g., logistics, marketplaces, or retail operations)
  • design and operate systems where inputs are noisy, incomplete, or rapidly changing—and where human behavior impacts outcomes
  • working with data science on optimization models, experimentation, and economically driven decision systems
  • Deep understanding of model limitations in production and the ability to design systems that account for feedback loops and unintended consequences
  • define clear direction, sequence investments, and make difficult tradeoffs in complex, ambiguous environments
  • partnering closely with operations teams to ensure systems reflect real-world constraints and drive measurable execution improvements
  • navigate and lead in environments where tradeoffs between speed, cost, and experience are constant and dynamic
  • Exceptional communication, influence, and cross-functional leadership skills
  • Systems thinker with strong judgment and the ability to translate complexity into clear, actionable strategy

Nice to have

  • AI/ML expertise

What the JD emphasized

  • advanced optimization
  • real-time decisioning
  • applied AI at massive scale
  • optimization and AI
  • real-time operational signals
  • horizontal AI platforms
  • real-time, high-stakes decisioning
  • live, large-scale system
  • optimization and ML systems
  • dynamic marketplace
  • massive scale
  • real-time responsiveness
  • marketplace volatility
  • noisy or incomplete data
  • non-stationary demand
  • tightly coupled system dynamics
  • optimization gains
  • foundational improvements
  • new capabilities
  • highly constrained and dynamic environment
  • optimization models
  • economically driven decision systems
  • model limitations in production
  • feedback loops
  • unintended consequences
  • complex, ambiguous environments
  • real-world constraints
  • measurable execution improvements
  • ambiguity
  • tradeoffs between speed, cost, and experience
  • scale
  • technical depth
  • real-world impact
  • large-scale decision systems
  • complex marketplace problems
  • extraordinary scale

Other signals

  • AI/ML at massive scale
  • optimization and real-time decisioning
  • horizontal AI platforms
  • live, large-scale system evolution