Kubernetes Platform Engineering Manager – Self-Service & AI

NVIDIA; California (MO); On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA’s DGX Cloud Kubernetes Platform & Production Engineering team seeks an Engineering Manager to lead customer delivery and self-service for production Kubernetes clusters. You will own end-to-end delivery from intake to handoff, driving automation and visibility across multiple teams.

We value 8+ years of industry experience with leadership, strong Kubernetes and cloud infra knowledge, and a track record delivering scalable, automated solutions.

Qualifications

• 8+ years in software or production engineering with leadership experience.
• Experience building platform APIs, self-service infrastructure, or onboarding systems.
• Strong Kubernetes, cloud infra, and distributed systems knowledge.
• Hands-on AI tool usage and AI-enabled workflows.
• Ability to translate customer needs into automated, scalable solutions.
• Proven cross-functional leadership, prioritization, and judgment.

Responsibilities

• Lead a team of engineers delivering production Kubernetes clusters for AI workloads from intake to handoff.
• Turn recurring tasks into automated self-service workflows via APIs and tooling.
• Define roadmaps, staffing plans, and ownership while mentoring leaders.
• Collaborate across platform, runtime, release, security, TPM, and infra groups.
• Establish interfaces and measure delivery speed, readiness, and customer visibility.

Skills

Leadership

Kubernetes

Cloud infrastructure

Distributed systems

Automation

AI tools

Cross-functional collaboration

Education

BS in Computer Science / Engineering

MS in Computer Science / Engineering

Tools

Terraform

GitOps

CI/CD

Job description

NVIDIA’s DGX Cloud Kubernetes Platform & Production Engineering team seeks an Engineering Manager to lead customer delivery and self-service for production Kubernetes clusters. You will own end-to-end delivery from intake to handoff, driving automation and visibility across multiple teams.

We value 8+ years of industry experience with leadership, strong Kubernetes and cloud infra knowledge, and a track record delivering scalable, automated solutions.