Staff Technical Project Manager, ADAS

We are CARIAD, an automotive software development team with the Volkswagen Group. Our mission is to make the automotive experience safer, more sustainable, more comfortable, more digital, and more fun. To achieve that we are building the leading tech stack for the automotive industry and creating a unified software platform for over 10 million new vehicles per year. We’re looking for talented, digital minds like you to help us create code that moves the world. Together with you, we’ll build outstanding digital experiences and products for all Volkswagen Group brands that will transform mobility. Join us as we shape the future of the car and everyone around it.

​Role Summary:

The Staff Technical Project Manager for Automated Driving leads the planning activities for CARIAD’s US-based automated driving workstream, with a primary focus on ML-driven L2++ / L3 capability development, integration, and validation.

This role supports the local engineering teams developing core automated driving capability and ensures tight coordination across model development, data workflows, evaluation, system integration, and in-vehicle deployment.

In addition to program management, this role also acts as the agile delivery lead for the team: driving execution cadence, facilitating prioritization and planning, removing blockers, and helping the team operate effectively in a fast-moving and ambiguous environment.

Furthermore, this role helps enable the effective use of GenAI and agentic AI for development by coordinating tooling access, infrastructure readiness, and local adoption formats in partnership with engineering, IT, and other support functions.

The Staff Technical Project Manager serves as a key coordination bridge across US and international engineering teams, ensuring milestones, dependencies, interfaces, and decisions are clearly owned and executed. Alongside technical execution, this role maintains visibility across program risks, resource needs, and budget topics, and ensures leadership has clear, actionable reporting.

Role Responsibilities:

Program structure, milestones & dependency management

• Own program structure, milestones, dependency management, and risk tracking for the US automated driving development program.
• Coordinate cross-site dependencies with partner engineering teams; ensure interface contracts, deliverables, and integration handoffs are explicit and tracked.
• Help translate evolving engineering work into a clear and executable delivery plan, balancing near-term milestones with longer-term capability build-up.

Technical execution across ML and vehicle integration

• Drive execution across model development, data workflows, evaluation, system integration, and in-vehicle deployment.
• Ensure integration readiness through clear entry/exit criteria, validation plans, and tracked closure of integration issues.
• Align system-level interfaces, build integration plans, and coordinate multi-team delivery for vehicle releases.

Agile delivery leadership

• Establish and run the team’s execution cadence, including planning, backlog refinement, dependency tracking, and regular progress reviews.
• Act as Agile Delivery Lead / Scrum Master by facilitating ceremonies, improving team operating rhythm, identifying blockers early, and driving timely resolution.
• Support prioritization decisions and maintain a healthy, actionable backlog aligned to program milestones.

Reporting, risk management & resource tracking

• Maintain structured reporting and clear escalation paths for engineering and leadership stakeholders.
• Track program actuals versus plan across headcount, compute, tooling, and supplier support; surface deviations early and support planning decisions.
• Own RAID (risks, assumptions, issues, dependencies) discipline and drive mitigation plans to closure.

GenAI/Agentic AI enablement & productivity initiatives

• Enable effective use of GenAI and agentic AI development tools by coordinating access, tooling, infrastructure, and process readiness with internal partners.
• Drive local AI productivity initiatives such as workflow pilots, hackathons, and best-practice sharing to improve engineering efficiency and effectiveness.

​General Skills:

• Strong communi