Lead Product Manager, Autonomy

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

We are seeking a Lead Product Manager to lead the strategy and execution of the core autonomy stack that powers the Waabi Driver. This role is central to the success of the business and requires a leader who can bridge the gap between cutting-edge AI research and real-world commercial requirements. You will provide focused ownership and coordination across teams, ensuring that autonomy efforts are aligned with both technical milestones and driverless launch objectives. You will bring the strategic depth and execution rigor needed to manage complexity at this scale, turning advanced autonomy capabilities into a reliable, commercial product.

You Will...

- Define, develop and execute the Autonomy roadmap, aligning core driving capabilities with the company’s driverless and commercial milestones across both the trucking and robotaxi verticals.

- Drive the end-to-end product lifecycle for autonomy features by translating complex use cases into actionable requirements and establishing performance benchmarks for deploying core driving behaviors in the real world.

- Lead cross-functional alignment across Engineering, Design, Research, Simulation, Systems Engineering, Safety, and Commercial teams to define product requirements, manage technical trade-offs, and develop frameworks that make autonomy performance measurable and transparent.

- Analyze performance data and feedback from simulation, track, and road testing to develop a comprehensive understanding of system readiness metrics and systematically prioritize issue resolution.

- Be a team player who prioritizes trust, transparency, and honesty, leading by example in a high-stakes, safety-critical environment.

- Monitor key performance indicators (KPIs) such as ODD coverage, system readiness, and route viability to make data-driven decisions that accelerate commercialization.

Qualifications:

- Minimum of 8+ years of experience in a Product Management role, with a proven track record in autonomous vehicles, robotics, or complex AI/ML systems.

- Strong analytical and problem-solving skills to resolve dependencies, inform strategic decisions, and evaluate tradeoffs between performance and safety.

- Excellent communication and interpersonal skills, with significant experience drafting written strategy documents and slides to communicate complex autonomy concepts to diverse stakeholders.

- Demonstrated leadership abilities, with experience driving results and cross-functional alignment in fast-paced, high-growth environments.

- Exhibits exceptional empathy, fostering a deep understanding of the needs of internal engineering teams, safety drivers, and commercial partners.

- Adaptable and versatile, proficient at navigating the shift from R&D-heavy environments to product-driven commercial execution.

- Able to maintain progress towards long-term architectural goals while solving immediate operational hurdles.

- Passion for autonomous systems, safety-critical software, and building the "brain" of the vehicle that will redefine the future of freight.

Bonus:

- Deep understanding of the autonomy stack (e.g. Perception, Prediction, Motion Planning, Localization) and the nuances of autonomous driving operations.

- Experience defining operational boundaries and safety validation milestones to drive the successful deployment of autonomous features in complex environments.

- Technical experience in autonomous vehicle development or a background in Computer Science/Robotics.

- Experience working in an Agile/Scrum environment tailored for deep-tech research.