6d ago
New

Head of Global Customer Engineering - Internal EDA Infrastructure

6 Locationsexecutive
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Quick Summary

Key Responsibilities

Build the leaders.

Requirements Summary

12+ overall years building and leading engineering support organizations, spanning reactive and proactive customer engineering.

Technical Tools
Other

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.

Responsibilities

~1 min read
  • →

    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.

Requirements

~1 min read
  • 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.

  • 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.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is seeking exceptional individuals like you to help us drive the next wave of artificial intelligence.

NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you!

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 October 15, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Location & Eligibility

Where is the job
Not specified
Location terms not specified
Who can apply
Same as job location

About this job

Posted
6 days ago
Employer
has 2,192 open jobs on Jobera.

Listing Details

Posted
October 12, 2026
First seen
October 18, 2026
Last seen
October 18, 2026

Posting Health

Days active
0
Repost count
0
Trust Level
27%
Scored at
October 18, 2026

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Head of Global Customer Engineering - Internal EDA Infrastructure