Global Customer Engineering Lead, Kubernetes & AI Platform

NVIDIA Corporation; Northern (KY); Hybrid; USD 272,000 - 489,000; Full time

Job summary

NVIDIA invites an engineering leader to build Global Customer Engineering for Internal EDA Infrastructure, linking chip designers with the platforms they run on. The role spans multiple teams and requires developing managers and technic al leads across a globally distributed organization.

You will shape a world-class customer engineering function, run a first-class Kubernetes platform as a service, and advance an AI-powered support layer to reduce human queue volume while maintaining top-tier

Qualifications

• 12+ years leading engineering support organizations.
• 5+ years leading a globally distributed team.
• Influences roadmaps from support trends and engineering requirements.
• Deep familiarity with Kubernetes, EDA workloads, job schedulers, AI/LLM infra.
• Automation/AI experience to reduce ticket volume.
• Excellent communication with engineers and executives.
• Bachelor’s degree in engineering or equivalent.

Responsibilities

• Build and develop a globally distributed customer-facing engineering organization.
• Lead the Kubernetes platform team as a top-tier service with availability and roadmap ownership.
• Progress the L0 AI support layer from FAQ bot to issue-resolving system.
• Define and defend SLOs and secure stakeholder buy-in.
• Drive deep support and automation across EDA schedulers and internal LLM harnesses.

Skills

People leadership

Kubernetes

AI/LLM infra

Automation

Communication

Cross-functional collaboration

Education

Bachelor's degree in engineering

Tools

LSF

Slurm

Kubernetes

Job description

NVIDIA invites an engineering leader to build Global Customer Engineering for Internal EDA Infrastructure, linking chip designers with the platforms they run on. The role spans multiple teams and requires developing managers and technic al leads across a globally distributed organization.

You will shape a world-class customer engineering function, run a first-class Kubernetes platform as a service, and advance an AI-powered support layer to reduce human queue volume while maintaining top-tier