NVIDIA

NVIDIA

Posted via Workday

Senior Systems Engineer, Storage - DGX Cloud

Posted Aug 5, 2026

Role at a glance

Salary
$208K – $414K/yr
Location
5 Locations, California, United States
Work arrangement
On-site
Employment
Full-time
Experience
12+ years of practical experience.
Education
BS degree (or equivalent experience) in Computer Science or related technical field involving coding.

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Role Summary

AI-generated

This Systems Engineering role supports NVIDIA’s internal and external GPU cloud services, with a focus on reliable deployment, end-to-end observability, automation, and continuous improvement. The role operates Kubernetes-based storage and data platforms and builds tooling that improves production reliability, efficiency, and velocity.

What You'll Do

  • Design, deploy, and operate Kubernetes solutions for large-scale storage and data platforms, including manifests, Helm charts, and...
  • Build tools, services, and automation for provisioning, configuration, deployment, scaling, and day-2 operations of storage and data...
  • Develop and operate metrics, logging, tracing, dashboards, and alerting for production systems.
  • Diagnose and resolve complex issues across distributed, containerized infrastructure using analytical troubleshooting.
  • Scale systems through automation, infrastructure-as-code, and CI/CD while improving reliability and velocity.
  • Support services through deployment automation, capacity planning, launch and readiness reviews, incident response, postmortems, and...

Generated from the employer's posting. Verify important details before applying.

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Qualifications

BS degree or equivalent experience in Computer Science or a related technical field involving coding; 12+ years of practical experience; production Kubernetes experience; experience building storage, data, or platform infrastructure tools and services; observability experience with Prometheus, InfluxDB, Grafana, and the Elastic stack; proficiency in Python, Go, or Java; knowledge of Ansible, Chef, Puppet, ArgoCD, Git Pipelines, or Terraform; strong analytical troubleshooting skills.

Required

  • BS degree or equivalent experience in Computer Science or a related technical field involving coding
  • 12+ years of practical experience
  • Hands-on experience deploying, configuring, and operating Kubernetes workloads and solutions in production
  • Experience building tools and services for storage, data, or platform infrastructure
  • Solid software design fundamentals including algorithms, data structures, and complexity analysis on large-scale Linux-based systems
  • Experience building and operating telemetry and observability using Prometheus, InfluxDB, Grafana, and the Elastic stack
  • Strong analytical troubleshooting skills with a systematic, root-cause-driven approach
  • Proficiency in Python, Go, or Java

Preferred

  • Customer-first mindset focused on customer satisfaction and customer success
  • Experience with Git, code review, pipelines, and CI/CD
  • Experience using or running large private and public cloud systems based on Kubernetes, OpenStack, and Docker
  • Interest in crafting, analyzing, and fixing large-scale distributed systems
  • Experience designing storage- or data-focused tooling and automating operations at scale
  • Ability to thrive in collaborative environments and adapt to different working styles

Original job description

Content provided by the employer

Systems Engineering is an engineering discipline focused on building, automating, and operating the platforms and tooling that deliver large-scale production systems with high efficiency, reliability, and velocity. It combines software and systems engineering practices across infrastructure automation, containerized platforms, storage, telemetry, and observability. Systems engineers are highly specialized and possess expertise across domains such as Kubernetes and container orchestration, infrastructure-as-code, CI/CD, storage systems, monitoring, and analytical troubleshooting. Their responsibilities center on deploying and operating reliable, automated platforms and on building the tools and services that keep storage and data infrastructure healthy and performant.

Our team at NVIDIA ensures that our internal and external facing GPU cloud services are deployed reliably, observable end-to-end, and continuously improved through automation. We enable developers to ship changes safely through repeatable CI/CD pipelines and Kubernetes-based deployments while keeping an eye on capacity, latency, and performance. A core part of this work is an SRE mindset: eliminating manual toil through automation, building self-service tooling, and growing the efficiency of production systems. We use a breadth of tools and approaches to tackle a broad spectrum of problems, and practices such as blameless postmortems, proactive identification of failure modes, and iterative improvement are key to product quality and to an interesting, dynamic day-to-day. Our culture of diversity, intellectual curiosity, problem-solving, and openness is important to our success. Our organization brings together people with a wide variety of backgrounds, experiences, and perspectives. We encourage them to collaborate, think big, and take risks in a blame-free environment. We promote self-direction to work on meaningful projects while striving to build an environment that provides the support and mentorship needed to learn and grow.
 

What You Will Be Doing:

  • Design, deploy, and operate solutions on Kubernetes for large-scale storage and data platforms, including the manifests, Helm charts, and operators that run them.

  • Build tools, services, and automation that improve the lifecycle of storage and data systems – from provisioning and configuration through deployment, scaling, and day-2 operations.

  • Develop and operate telemetry and observability for production systems – metrics, logging, tracing, dashboards, and alerting – so that system health, availability, and latency are measurable and actionable.

  • Apply strong analytical troubleshooting skills to diagnose and resolve complex issues across distributed, containerized infrastructure.

  • Work closely with peers and partner teams to improve the lifecycle of services, from inception and design through deployment, operation, and refinement.

  • Scale systems sustainably through automation, infrastructure-as-code, and CI/CD, and evolve systems by pushing for changes that improve reliability and velocity.

  • Support services before they go live through activities such as deployment automation, capacity planning, and launch and readiness reviews.

  • Practice sustainable incident response and postmortems, and participate in an on-call rotation to support production systems.

What We Need To See:

  • BS degree (or equivalent experience) in Computer Science or related technical field involving coding.

  • 12+ years of practical experience.

  • Hands-on experience with Kubernetes – deploying, configuring, and operating workloads and solutions on Kubernetes in production.

  • Experience building tools and services for storage, data, or platform infrastructure, with solid software design fundamentals (algorithms, data structures, complexity analysis) on large-scale Linux-based systems.

  • Experience building and operating telemetry and observability using tools such as Prometheus, InfluxDB, Grafana, and the Elastic stack.

  • Strong analytical troubleshooting skills with a systematic, root-cause-driven approach to identifying and resolving complex problems.

  • Proficiency in one or more of the following: Python, Go, or Java.

  • Good knowledge of infrastructure configuration management and infrastructure-as-code tools such as Ansible, Chef, Puppet, ArgoCD, Git Pipelines, and Terraform.

Ways to Stand Out from the Crowd:

  • Customer-first mindset with a focus on customer satisfaction and a passion for ensuring customer success.

  • Experience with Git, code review, pipelines, and CI/CD. Experience using or running large private and public cloud systems based on Kubernetes, OpenStack, and Docker.

  • Interest in crafting, analyzing, and fixing large-scale distributed systems, with strong debugging skills and a systematic problem-solving approach.

  • Experience designing storage- or data-focused tooling and automating their operations at scale.

  • Thrive in collaborative environments and enjoy working with various teams, and are flexible in adapting to different working styles.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 333,500 USD for Level 5, and 256,000 USD - 414,000 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 18, 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.

NVIDIA

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.