Every NVIDIA GPU starts as a job on our internal EDA infrastructure. Thousands of hardware engineers designing next-generation silicon depend on it being fast, available, and frictionless and when it isn't, tapeout schedules feel it. This team is the difference. We're hiring a hands-on engineering leader to develop our Global Customer Engineering for Internal EDA Infrastructure - the organization sitting directly between our chip designers and the platforms they run on. This is a multi-team leadership role spanning managers and tech leads across a globally distributed organization, and it comes with two co-equal mandates: A world-class customer engineering organization for EDA infrastructure - reactive when it must be, proactive by design. The Kubernetes platform team that delivers one of our customer services end to end.
You will design software solutions, and automation pipelines to eliminate operational overhead. When encountering recurring toil for customer engineering, your immediate impulse is to engineer permanent automated remedies. Staying directly connected to live production environments is essential hence the end-to-end Kubernetes platform responsibility.
What You'll Be Doing:- Build the leaders. Grow and develop the leaders running a globally distributed team of customer-facing engineers who own the reactive support queue for EDA infrastructure - escalating into service engineering with clean, high-quality signal.
- Develop the Kubernetes platform. Run the K8s platform team as a first-class customer engineering service: availability, roadmap, developer experience, and the operational excellence behind it.
- Ship the L0 AI support layer. Own the evolution of our AI support agent from FAQ bot to a system that safely resolves real issues against real internal systems - and measurably removes volume from human queues.
- Set the bar. Define and defend SLOs for operational performance, and win genuine stakeholder buy-in.
- Stay close to the metal. Drive deep support and continuous improvement across EDA job schedulers (LSF/Slurm), Kubernetes platforms, and the internal LLM harnesses our chip designers depend on.
What We Need To See:- 12+ overall years building and leading engineering support organizations, spanning reactive and proactive customer engineering.
- 5+ years of experience leading a globally distributed organization, including developing managers and leaders.
- Proven ability to influence technical roadmaps by turning support trends into engineering requirements that actually ship.
- Deep technical familiarity with Kubernetes, EDA workloads, job schedulers, and AI/LLM infrastructure foundations.
- Track record of leveraging automation and AI/ML to improve support efficiency and drive ticket volume down.
- Exceptional communication skills - credible with individual engineers and executive leadership in the same day.
- A Bachelor's degree in a relevant engineering field or equivalent experience.
Ways To Stand Out from the Crowd:- Led a platform team and a customer facing team simultaneously, and made each one better because of the other.
- You've architected "self-healing" support ecosystems where a customer engineering team builds and owns the tools it runs on including "shift-left" tooling that resolved issues before a ticket ever existed.
- You've led the full lifecycle of generative AI / LLM-based support assistants, well beyond basic chatbots, into systems that integrate deeply and safely with internal infrastructure.
- Run LSF, Slurm, or Kubernetes at a scale where manual intervention was the bottleneck and you personally led the automation that removed it.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD for Level 4, and 320,000 USD - 488,750 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until September 19, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
