Head of Global Customer Engineering - Internal EDA Infrastructure

Job Title

Head of Global Customer Engineering - Internal EDA Infrastructure

Role Summary

Lead a globally distributed customer engineering organization that sits between chip designers and internal EDA platforms. The role combines people leadership across multiple teams with hands-on ownership of an end-to-end Kubernetes platform and automation to remove operational toil.

This position is accountable for availability, operational excellence, and evolving support tooling (including AI-driven support) to reduce human queue volume and accelerate tapeout schedules.

Experience Level

Senior level. The posting requests 12+ years building and leading engineering support organizations and 5+ years leading globally distributed teams.

Responsibilities

You will run a multi-team organization responsible for reactive customer support and a first-class Kubernetes platform service. Key responsibilities include:

• Grow and develop managers and technical leaders across a global, customer-facing engineering organization.
• Operate and drive the roadmap, availability, developer experience, and operational excellence of the Kubernetes platform used by EDA workloads.
• Design and deliver software and automation pipelines to eliminate recurring operational overhead and reduce manual toil.
• Own the evolution and production safety of an AI-driven L0 support agent that removes volume from human queues.
• Define, defend, and drive adherence to SLOs for operational performance and obtain stakeholder buy-in.
• Provide deep technical support and continuous improvement across EDA job schedulers (LSF/Slurm), Kubernetes platforms, and internal LLM/AI harnesses.

Requirements

Must-have qualifications and skills:

• 12+ years building and leading engineering support organizations combining reactive and proactive customer engineering.
• 5+ years leading a globally distributed organization with experience developing managers and leaders.
• Proven ability to convert support trends into actionable engineering requirements and influence technical roadmaps.
• Deep technical familiarity with Kubernetes, EDA workloads, job schedulers, and AI/LLM infrastructure fundamentals.
• Track record of leveraging automation and AI/ML to improve support efficiency and reduce ticket volume.
• Exceptional communication skills with the ability to engage individual contributors and executive leadership effectively.

Nice-to-have:

• Experience running a platform team and a customer-facing team simultaneously to mutual benefit.
• Architected self-healing support ecosystems or "shift-left" tooling that prevented tickets.
• Led the full lifecycle of generative AI / LLM-based support assistants integrated safely with internal systems.
• Hands-on experience operating LSF, Slurm, or Kubernetes at scale and driving automation to remove manual intervention.

Education Requirements

Bachelor's degree in a relevant engineering field or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.