This role pays more than
97%
of similar roles. Most pay
$177,087–$261,375
— the shaded band above.
At the midpoint, this role pays about
$352k
versus about
$219k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
867 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 849 roles with salary data.
Head of Global Customer Engineering - Internal EDA Infrastructure leads a multi-team, globally distributed organization focused on the internal EDA infrastructure used by hardware engineers to design silicon. This leadership role involves managing managers and technical leads to build a world-class customer engineering organization while simultaneously running the Kubernetes platform team as a first-class service. The successful candidate will develop software solutions and automation pipelines to eliminate operational toil, manage the evolution of an AI support layer for internal systems, and define performance SLOs. Key responsibilities include overseeing EDA job schedulers like LSF and Slurm, managing Kubernetes platforms, and maintaining LLM harnesses. Required expertise includes extensive experience in engineering support organizations, Kubernetes, EDA workloads, and leveraging AI/ML to improve efficiency. The role solves critical infrastructure challenges to ensure seamless chip design workflows for internal hardware teams.
Lead and develop a globally distributed team of managers and technical leads for EDA infrastructure support.
Manage the Kubernetes platform team to ensure high availability, roadmap execution, and developer experience.
Design software solutions and automation pipelines to eliminate recurring operational toil for customer engineering.
Evolve the AI support agent into a system that safely resolves real issues against internal systems.
Define and defend service level objectives (SLOs) for operational performance across all platforms.
Drive continuous improvement for EDA job schedulers, Kubernetes platforms, and internal LLM harnesses.
Translate customer support trends into actionable engineering requirements to influence technical roadmaps.
What we're looking for
Experience building and leading engineering support organizations across 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.
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 reduce ticket volume.
Exceptional communication skills for interacting with both individual engineers and executive leadership.
Bachelor’s degree in a relevant engineering field or equivalent experience.
Experience leading platform and customer-facing teams simultaneously, architecting self-healing ecosystems, or managing large-scale LSF/Slurm/Kubernetes environments (preferred).
AI
Deep Learning
SoC
Firmware
Hardware Design
TME) engineering
Robotic s
Power Efficiency
Thermomechanical Integration
Sensors Validation
NPI
Project Management