Senior Product Manager, Operations & Commercialization

Required

• Own the product roadmap for Operations & Commercialization by translating the needs of operators, field teams, merchants, customers, and commercial partners into high-impact priorities.
• Define and own success measures for operational performance and delivery quality including successful and on-time deliveries, customer and merchant defects, reliability, supply hours, fleet utilization, and cost efficiency; establish baselines and targets and make performance visible by market, partner, and platform where useful.
• Maintain an evidence-based view of the most important failure modes and opportunities using operational data, customer and partner feedback, and field observation to identify root causes, shape requirements, and reassess priorities as evidence changes.
• Build scalable operational workflows for robot supervision, deployment, and dispatch that reduce manual work and improve fleet productivity.
• Improve delivery reliability with capabilities for issue detection, remote interventions, exception handling, incident follow-up, and service recovery that maximize successful deliveries.
• Elevate the customer and public experience through intuitive, dependable interactions that strengthen merchant satisfaction and help make Serve robots welcome in neighborhoods; spend time with operators, field teams, merchants, and customers to ground decisions in real workflows.
• Enable commercial launches by partnering with the Logistics Platform team to define product capabilities, integration requirements, onboarding workflows, and SLA guardrails that streamline launches and drive partner success.
• Scale market deployments with repeatable product capabilities and workflows that accelerate launches, reduce operational complexity, and support expansion.
• Own products from concept through launch and iteration by defining problem statements, requirements, success criteria, rollout plans, and adoption measures; align teams, make tradeoffs, and ensure successful rollout.
• Drive fast, focused execution with Engineering by scoping and sequencing improvements, favoring small releases, rapid learning, and frequent testing over unnecessary over-engineering while maintaining release readiness and reliability.
• Use analytics and AI-enabled tools where useful including LLM-based analysis or agents to explore operational data, accelerate root-cause investigation, and turn findings into actionable requirements and priorities; rapidly prototype workflows, dashboards, and proofs of concept to validate ideas before committing significant engineering capacity.
• Coordinate cross-functional quality initiatives with Analytics, Engineering, Operations, Program Management, Safety, Support, and Field Operations; keep owners, dependencies, risks, and decisions visible, escalate blockers early, and close the loop on defects and root causes.