Product Manager - Maps Guidance
The automotive industry is rapidly transforming as Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD) become standard across vehicle segments. At the core of these systems lies highly accurate, AI-generated map content that provides vehicles with critical context: legal speed limits, road curvature, lane-level topology, and rich 3D representations of the world.
At TomTom, we are redefining how maps are built, maintained, and consumed by leveraging AI, machine learning, and computer vision at scale. Our Orbis Maps for Automation power leading global automotive OEMs and are a cornerstone of TomTom’s strategy in automated driving.
As a Product Manager II in the Guidance domain, you own a clearly defined set of map features within a broader product area, supporting navigation and automated driving. You are accountable for value, quality, and delivery, working at the intersection of product strategy, AI-driven production systems, and customer impact. This role goes beyond feature definition: you actively shape how AI changes map creation, quality measurement, and product decision-making.
What you'll do
Product Ownership & Strategy
- Own and evolve a portfolio of map features used by Navigation and ADAS/AD systems, from problem discovery through scaled delivery.
- Translate product strategy into clear outcomes, measurable success criteria, and prioritized roadmaps.
- Balance customer value, technical feasibility, and AI-driven production constraints in decision-making.
AI-Driven Product Development
- Define product and data requirements for AI-based mapmaking pipelines, including training data needs, quality signals, and feedback loops.
- Partner with engineering and data science to operationalize AI models into reliable, scalable product capabilities.
- Use AI-assisted insights to accelerate discovery, quality assessment, and root-cause analysis.
Quality, Metrics & Outcomes
- Define and track product and data quality metrics (coverage, accuracy, freshness, confidence) relevant for ADAS and AD use cases.
- Drive a shift from manual or rule-based validation to model-based and statistically driven quality evaluation.
- Be accountable for release readiness and real-world performance of your features.
Stakeholder & Customer Collaboration
- Work closely with engineering, operations, data science, UX, and commercial teams to align scope, timelines, and outcomes.
- Engage with internal and external customers (including automotive OEMs) to understand use cases, constraints, and success criteria.
- Clearly communicate trade-offs, risks, and progress to stakeholders at different levels.
Continuous Improvement
- Develop deep understanding of TomTom’s map production systems and identify opportunities to improve efficiency, scalability, and cost through AI.
- Contribute to evolving product management practices in an organization increasingly shaped by AI-first ways of working.
What you'll need
Experience & Skills
- 3–5+ years of experience in Product Management, ideally in data-intensive, platform, or technical product environments.
- Strong ability to structure complex problems, reason with data, and make clear prioritization decisions.
- Experience working with engineering-heavy teams; familiarity with AI/ML concepts is a strong advantage (hands-on modeling not required).
- Ability to define metrics and success criteria and use them to steer product decisions.
Ways of Working
- Comfortable operating in ambiguity and change, with curiosity for how AI reshapes products and roles.
- Strong communicator who can translate between technical depth and customer impact.
- Bias for ownership, learning, and continuous improvement.
Mindset & Values
- Alignment with TomTom’s leadership principles: Ownership, Impress the Customer, Better Every Day, and collaboration at scale.
- Motivation to grow as a PM in an environment where AI augments decision-making, execution, and impact.
