Engineering Manager, Kubernetes Customer Delivery and Self-Service

NVIDIA; Washington; On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA in Washington state seeks an Engineering Manager to lead the Customer Delivery and Self‑Service function for the DGX Cloud Kubernetes Platform and Production Engineering team. You will steer end‑to‑end delivery of production Kubernetes clusters for AI workloads, from request through enablement and handoff.

You’ll build and mentor a team, define roadmaps, automate workflows, and partner with platform, runtime, security, TPM, and infra groups to deliver scalable, self‑service solutions.

Qualifications

• 8+ years of industry experience, including 2+ years leading or managing engineers.
• Experience building platform APIs, self-service infrastructure, workflow automation, developer platforms, or customer onboarding systems.
• Strong understanding of Kubernetes, cloud infrastructure, distributed systems, or production engineering.
• Hands-on experience using AI coding tools and AI-enabled engineering workflows.

Responsibilities

• Lead a team of software and production engineers focused on Kubernetes customer delivery, onboarding, and self-service.
• Own end-to-end delivery of production Kubernetes clusters for AI workloads, from request through enablement, validation, and handoff.
• Drive a coordinated delivery plan with clear owners, dependencies, readiness gates, timelines, risks, and blockers.
• Partner across platform, runtime, release, fleet operations, CSE, product, TPM, security, and infrastructure teams.

Skills

Kubernetes & cloud infrastructure

Leadership & cross-functional

Workflow automation

AI-enabled engineering workflows

System integration

Education

BS or MS in Computer Science/Engineering

Tools

Terraform

GitOps

APIs & workflow engines

Job description

NVIDIA’s DGX Cloud Kubernetes Platform & Production Engineering team is seeking an Engineering Manager to develop and guide our Customer Delivery and Self-Service function. This group will manage the entire engineering delivery process from an approved customer request through platform enablement, cluster build, validation, and handoff. The leader will also transform the current cross-team process into a scalable, automated, self-service solution.

What You’ll Be Doing

• Build and lead a team of software and production engineers passionate about Kubernetes customer delivery, onboarding, and self-service.
• Own end-to-end delivery of production Kubernetes clusters for AI workloads, from accepted request through enablement, qualification, validation, and customer handoff.
• Drive a coordinated delivery plan with clear owners, dependencies, readiness gates, timelines, risks, status, and blocking issues.
• Partner across platform, runtime, release, fleet operations, CSE, product, TPM, security, and infrastructure teams.
• Build integrations connecting customer intake and status systems with Kubernetes provisioning, access, validation, and production acceptance.
• Turn recurring delivery tasks into detailed, automated self-service workflows using APIs, AI tools, and agents.
• Define service interfaces and measure and improve delivery speed, readiness, automation, recovery, and customer visibility.
• Set the team’s roadmap, staffing, and operational ownership while hiring, mentoring, and developing technical leaders.

What We Need To See

• 8+ overall years of industry experience, including 2+ years leading or managing engineers.
• Experience building platform APIs, self-service infrastructure, workflow automation, developer platforms, or customer onboarding systems.
• Strong understanding of Kubernetes, cloud infrastructure, distributed systems, or production engineering.
• Hands-on experience using AI coding tools and AI-enabled engineering workflows.
• Experience integrating multiple systems and teams into a reliable end-to-end workflow.
• Ability to translate customer and operational requirements into clear technical interfaces and automated solutions.
• Strong cross-functional leadership, communication, customer empathy, prioritization, and judgment.
• BS or MS in Computer Science, Engineering, or equivalent experience.

Ways To Stand Out From The Crowd

• Experience building Kubernetes provisioning, infrastructure-as-code, service catalog, or internal developer platform capabilities.
• Familiarity with Terraform, GitOps, identity and access management, RBAC, APIs, workflow engines, and production-readiness automation.
• Experience with GPU infrastructure and AI-optimized Kubernetes clusters, including accelerated networking, high-performance storage, GPU scheduling, workload qualification, or large-scale fleet operations.
• A track record of reducing onboarding time and operational toil through automation and self-service.
• Experience combining strong platform engineering with an attitude centered on product development and customer needs.

Join us in transforming the future of computing and make an impact on the world!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 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.