Senior Systems Engineer, Storage - DGX Cloud

About the role

Systems engineers at NVIDIA are responsible for deploying and operating reliable, automated platforms for internal and external GPU cloud services. They build tools and services that improve the lifecycle of storage and data systems, and apply strong analytical troubleshooting skills to diagnose and resolve complex issues.

Responsibilities

• Design, deploy, and operate solutions on Kubernetes for large-scale storage and data platforms.
• Build tools, services, and automation that improve the lifecycle of storage and data systems.
• Develop and operate telemetry and observability for production systems.
• Apply strong analytical troubleshooting skills to diagnose and resolve complex issues.
• Support services before they go live through deployment automation, capacity planning, and launch and readiness reviews.
• Practice sustainable incident response and postmortems, and participate in an on-call rotation.

Requirements

• 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.
• 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.

Qualifications

• A 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.
• Thriving in collaborative environments and enjoying working with various teams, and being flexible in adapting to different working styles.

Benefits

NVIDIA offers competitive compensation, including a base salary range of $208,000 - $333,500 for Level 5 and $256,000 - $414,000 for Level 6, along with equity and benefits. Applications are accepted until July 9, 2026.

Schedule

Our team works in a hybrid model, combining remote and in-office work.

Pay

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

Skills

Strong analytical troubleshooting skills, hands-on experience with Kubernetes, proficiency in programming languages like Python, Go, or Java, and experience with infrastructure configuration management tools.

Benefits

Competitive compensation, including base salary, equity, and benefits. Hybrid work schedule, professional development opportunities, and a supportive, diverse workplace culture.