Engineering Manager, Kubernetes Customer Delivery and Self-Service

NVIDIA•Washington, DC

1d•$224,000 - $356,500

About The Position

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.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.