Product Manager - Physical AI

ANYbotics is transforming industrial plants in the energy, process, and utility sectors by introducing autonomous, high-mobility robots to novel, challenging applications. As we continue to scale the capabilities of the ANYmal platform, we are seeking a Product Manager for Physical AI.

In this role, you will be the bridge between our commercial goals, our strategic product vision and our world-class robotics engineering teams. You will act as the "engine room" for the product, deeply integrating with teams focused on perception, navigation, behavior, and locomotion to ensure our autonomy roadmap is not only technically feasible but also pushes the boundaries of what is possible in the field and moves the needle to meet the evolving demands of our key industrial customers.

• Roadmap Execution: Partner closely with the VP Robotics and the Product organization to translate strategic portfolio goals into detailed technical roadmaps. Take ownership of the "how" and "when" for prioritizing, communicating and ensuring successful deployment improvements across perception, behavior, navigation, and locomotion.

• Commercial Value Driven: Integrate key account insights into the product roadmap to align development priorities with customer business value and drive key metrics

• Autonomy Strategy: Define and manage the detailed product strategy to improve Resilience & Reliability and Coverage. Create clear value propositions to move the metrics for key customers and turn those into requirements including the Operational Design Domain (ODD) to guide engineering efforts and ensure resilient and robust robot behavior in complex industrial environments.

• Cross-Functional Technical Leadership: Work daily with R&D teams (Perception, Navigation, Locomotion) to translate product needs into functional specifications. Act as the primary product point of contact, ensuring that engineering trade-offs are balanced against customer value.

• Performance Optimization: Drive the continuous improvement of robot reliability and safety. Establish KPIs for robot performance (e.g., success rates, intervention frequency, navigation efficiency) and lead efforts to identify and remediate bottlenecks.

• Technical Risk Management: Anticipate technical challenges and edge cases within the autonomy stack. Proactively identify dependencies and risks early in the development lifecycle to ensure seamless integration between hardware capabilities and software features.

• Field & Engineering Bridge: Collaborate with field engineering to ensure features get deployed successfully at key accounts. Synthesize real-world performance data and issues into actionable product backlogs. Ensure that lessons learned from deployments directly inform the technical evolution of the autonomy stack.

• Deep Technical Background: Engineering or science degree with a strong focus on Robotics, Computer Science, or equivalent.

• Industry Business Expertise: Proven experience with Industrial customers and understanding what drives their business and needs for robotic inspection.

• Domain Expertise: Experience in one or more core robotics disciplines: perception, path planning (navigation), robot behavior, or advanced control/locomotion.

• Technical PM Experience: Experience in technical product management, ideally for complex hardware-software integrated products (e.g., autonomous vehicles, mobile robotics, or advanced consumer electronics).

• Operational Design Domain (ODD) Familiarity: Experience defining ODDs for robotic or autonomous systems and managing the safety and performance validation associated with them.

• Collaborative Mindset: Ability to communicate complex technical concepts effectively to both engineering teams and non-technical stakeholders.

• Outcome-Oriented: A proven ability to break down ambiguous, open-ended customer needs and requirements into concrete development sprints and deliverables.

• Systems Thinking: Ability to see the "big picture" of how software-driven behavior changes impact the physical robot hardware (and vice-versa).

• Practical experience working with real-world robotics deployments in industrial, unstructured, or outdoor environments.

• Experience with mission-critical systems or safety-certified development processes.

• Strong familiarity with modern robotics toolsets (ROS2, simulation environments, data-driven regression testing).