Senior Systems Engineer, Storage - DGX Cloud

NVIDIA is a leading technology company known for its innovative GPU cloud services. They are seeking a Senior Systems Engineer to design, deploy, and operate large-scale storage and data platforms, ensuring reliability and automation through Kubernetes and infrastructure practices.

Responsibilities:

• 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

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, 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
• 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