Senior Systems Engineer, Storage - DGX Cloud

Nvidia

Remote

Quick summary

Work type: Remote
Location: CANCILCOOR
Salary: $208,000–$333,500 / yr
Posted: 8 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $196k

This role $271k

$130k most similar roles pay here $355k

This role pays more than 89% of similar roles. Most pay $155,900–$235,750 — the shaded band above. At the midpoint, this role pays about $271k versus about $196k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 980 open roles on FindRole.

Listed pay typically runs $168,000–$270,250 across 966 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Systems Engineer, Storage - DGX Cloud

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As a senior systems engineer at NVIDIA, you will join a dynamic team responsible for deploying and operating reliable GPU cloud services. Your day-to-day responsibilities include designing Kubernetes-based solutions for large-scale storage and data platforms, building automation tools to streamline system lifecycles, and developing observability features using Prometheus, Grafana, and other monitoring tools. You will collaborate with cross-functional teams to improve service reliability through CI/CD pipelines and infrastructure-as-code practices, while also participating in on-call rotations to support production systems. The role requires hands-on experience with Kubernetes, proficiency in Python, Go, or Java, and strong analytical skills for troubleshooting complex issues across distributed infrastructures.

Skills

Kubernetes Python Go Terraform Prometheus Grafana CI/CD Ansible Docker Git Java InfluxDB Elasticsearch Helm ArgoCD

What you'll do

Design and deploy Kubernetes solutions for large-scale storage and data platforms.
Build automation tools to improve the lifecycle of storage and data systems.
Develop telemetry and observability for production systems using metrics and logging.
Analyze and troubleshoot complex issues in distributed, containerized infrastructure.
Scale systems sustainably through automation and CI/CD practices.
Support services pre-launch with deployment automation and capacity planning.

What we're looking for

12+ years of practical experience in systems engineering or related field.
Hands-on expertise with Kubernetes for deploying and operating workloads in production.
Experience building tools and services for storage and data infrastructure using Linux-based systems.
Proficiency in telemetry and observability tools like Prometheus, Grafana, and Elastic stack.
Strong analytical troubleshooting skills to diagnose complex issues in distributed systems.
Knowledge of infrastructure-as-code tools such as Ansible, Terraform, and Git Pipelines.
Customer-first mindset with a focus on customer satisfaction and success.