Role at a glance
- Salary
- $224K – $356.5K/yr
- Location
- 3 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ overall years of industry experience, including 2+ years leading or managing engineers.
- Education
- BS or MS in Computer Science, Engineering, or equivalent experience.
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Role Summary
The DGX Cloud Kubernetes Platform & Production Engineering team is hiring an Engineering Manager to lead the Customer Delivery and Self-Service function. The role oversees production Kubernetes cluster delivery for AI workloads and transforms cross-team delivery processes into scalable, automated self-service workflows.
What You'll Do
- Build and 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 from accepted request through enablement, qualification, validation, and...
- Drive coordinated delivery plans with 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 between customer intake and status systems and Kubernetes provisioning, access, validation, and production acceptance.
- Define service interfaces and measure and improve delivery speed, readiness, automation, recovery, and customer visibility.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
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.
Required
- Platform APIs
- Self-service infrastructure
- Workflow automation
- Developer platforms
- Customer onboarding systems
- Kubernetes
- Cloud infrastructure
- Distributed systems
Preferred
- Kubernetes provisioning
- Infrastructure-as-code
- Service catalog
- Internal developer platform capabilities
- Terraform
- GitOps
- Identity and access management
- RBAC
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.