Principal OEM Execution Lead, Autonomous Driving Solutions

About the role

Own the end-to-end execution that takes NVIDIA DRIVE Autonomous Driving Software (NDAS) from product definition to production deployment across major OEM vehicle lines. We are seeking an accomplished engineering execution leader to lead adaptation, integration, validation, and production readiness of NVIDIA Autonomous driving solution (NDAS) for strategic automotive OEMs. You will work between NVIDIA product and engineering teams and the OEM's vehicle, software, systems, and validation groups. The role involves converting an agreed feature set into a deliverable vehicle program. This entails clarifying requirements, coordinating interfaces and responsibilities, setting the engineering plan, building consistent productization workflows, and managing issue resolution. You will influence teams such as systems engineering, autonomous-driving development, platform software, functional safety, cybersecurity, quality, validation, release, and customer engineering. NVIDIA is building the accelerated computing platform for autonomous vehicles and physical AI. This role offers the opportunity to develop how a full-stack autonomous-driving product is industrialized with the world's leading automakers. You will turn advanced AI and software into safe, scalable, production vehicles. Join us and be part of something outstanding!

Responsibilities

• Lead NDAS execution with major OEMs across the full program lifecycle — from feature definition and technical alignment through vehicle integration, validation, launch, and production ramp — owning the coordinated engineering plan per vehicle line, including requirements, architecture, adaptation scope, achievements, staffing, validation strategy, release criteria, and production-readiness gates.
• Translate OEM vehicle requirements and use cases into clear commitments for NVIDIA teams, while ensuring OEM partners understand product capabilities, constraints, assumptions, and the work required on their side; build scalable, repeatable workflows for adapting NDAS to specific OEM platforms, vehicle architectures, sensor configurations, compute platforms, networks, and development processes.
• Drive multi-functional implementation across autonomous-driving features, systems, platform software, vehicle integration, functional safety, cybersecurity, validation, quality, release, and field engineering.
• Establish a rigorous operating cadence with actionable achievements, objective readiness metrics, risk and dependency management, decision logs, and clear paths for addressing customer concerns that block progress.
• Direct technical issue resolution across systems, safety, security, and development groups — determining root causes, clarifying ownership,