Senior/Staff Technical Product Manager, Operational Design Domain (ODD) Tools

Description

The company builds a fully autonomous, zero-emissions vehicle designed from the ground up for AI and for its customers, aiming to make mobility-as-a-service safer, cleaner and more enjoyable.

The Autonomy Development Platform team is a group of Technical Product Managers who build the foundational tools used to define, validate and scale driving behavior. They work with engineering teams across the company. Within the team, the Environmental Foundation pillar decides where vehicles drive and supplies the ground truth about the world they drive in.

The Operational Design Domain (ODD) planning platform is the single source of truth for where the company operates. It holds the versioned, milestone-aligned Plan of Record for each city, and converts geography, road attributes and operating policy into the areas vehicles are cleared to drive. Its outputs feed production maps, safety validation, mileage accumulation, rider service areas and data labeling, so it sits on the critical path for every software release and every new city launch.

Responsibilities

• Own the product vision and roadmap for the ODD planning platform, serving first the Driving Behavior Technical Product Managers who define driving areas, and also the Mapping, Safety, Data Science and Program Management teams that depend on those definitions.
• Keep every Plan of Record accurate, validated and traceable, and help scale ODD planning to dozens of cities as the company grows.
• Balance urgent milestone needs against long-term platform investment, holding a high quality bar because errors in this product carry safety implications.
• Align the roadmap with Release milestones and city expansion plans, and move ODD control from manual, annotation-heavy work toward scalable, policy-driven configuration.
• Define the validation gates, guardrails and traceability that keep each Plan of Record consistent with the map it applies to and with earlier milestones. With Safety and Data Science, set precision and recall targets for the road attributes that shape driving areas.
• Work closely with Driving Behavior, Mapping, Safety and Data Science teams to map their end-to-end workflows, and turn operational pain points into large gains in planning speed, data quality and decision-making.
• Manage the full product lifecycle: write clear PRDs, own prioritization and the backlog, and run alpha validation before features reach milestone workflows. Break large problems into incremental releases that deliver value early.
• With engineering leadership, staff the roadmap, set release quality gates and work to bring production regressions to zero. Surface capacity and quality risks early, backed by data.
• Act as the single point of contact for ODD planning, communicating roadmap, trade-offs and status to stakeholders and leadership, and declining requests with a better alternative when needed.
• Define, track and report KPIs such as adoption, Plan of Record accuracy, time saved and platform performance, and use the data to show impact and guide strategy.

Requirements

• 5+ years of Technical Product Management experience, ideally on complex, data-heavy internal tools or enterprise-scale platforms.
• Able to discuss system architecture and data models with senior engineers.
• A proven record of defining validation, metrics and quality bars for data that supports high-stakes decisions.
• A proven ability to ship incremental value against clear priorities while balancing near-term milestone needs with long-term roadmap and platform health.
• Strong stakeholder management and communication skills, including the ability to build consensus across organizations, secure engineering investment and create clarity without formal authority.
• Nice to have: deep technical fluency with geospatial data, road networks or map data models, APIs and data pipelines.
• Nice to have: experience developing AI/ML, robotics or autonomous vehicle products, especially ODD definition, geofencing or service area planning.
• Nice to have: hands-on work with GIS tools and spatial data (for example PostGIS or GeoJSON) and SQL-based analytics (for example Databricks).
• Nice to have: experience with automated data mining or ML-based attribute extraction at scale, such as with vision-language models.
• Nice to have: experience leading delivery with distributed engineering teams across time zones.