We are looking for a hands-on senior engineer to own the lifecycle and automation of the Kubernetes platform supporting GNI network systems. You will also provide production support for network services running on the platform, partnering with their engineering owners when issues or changes cross the platform boundary. You will take complex problems from design through production and remain accountable for the outcome. You will bring deep Kubernetes expertise and help establish consistent engineering practices across the US and Bangalore teams. This is a senior individual contributor role with end-to-end ownership and production responsibility.
What You’ll Be Doing:
Design, build, and operate the Kubernetes platform that powers GNI network automation, telemetry, and operations across data center, colocation, and cloud environments.
Own the lifecycle management for GNI Kubernetes environments, including cluster onboarding, upgrades, capacity, availability, and recovery.
Develop production-quality software and automation for cluster provisioning, validation, upgrades, remediation, and safe multi-cluster delivery through GitOps.
Provide production support for network services hosted on the platform, working with Network Automation and service teams that retain ownership of application architecture, code, and features.
Diagnose complex Kubernetes platform and hosted-service failures involving control-plane health, cluster networking, storage, scheduling, workload placement, and multi-cluster dependencies. Drive issues from initial signal through verified resolution.
Define production-readiness and observability standards for the platform and hosted network services, including health signals, capacity, alerts, runbooks, and recovery.
Participate in CFR’s production on-call rotation, including scheduled after-hours and weekend coverage. Lead incident response and recovery, then drive corrective actions to completion.
What We Need to See:
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
8+ years of experience building or operating production Kubernetes platforms, network infrastructure, or distributed systems.
Deep experience with Kubernetes at scale, including cluster lifecycle, upgrades, networking, storage, and recovery.
Proficiency in at least one general-purpose programming language, such as Go or Python.
Experience with GitOps, infrastructure as code, CI/CD, and automated production delivery.
Experience deploying and supporting network automation or telemetry services on Kubernetes.
Experience with production on-call, incident response, root-cause analysis, and driving corrective actions to completion.
Ways to Stand Out From the Crowd:
Strong knowledge of IP routing, data center fabrics, and cloud networking is a great plus.
Experience designing and operating large, multi-region Kubernetes fleets, including fleet-wide upgrades and recovery.
Hands-on experience with Cluster API (CAPI) and Metal3 for bare-metal provisioning, cluster lifecycle, machine remediation, and upgrades.
Experience building Kubernetes controllers or operators in Go using custom resources and reconciliation patterns. Experience designing or operating network automation and telemetry services on Kubernetes at global scale.
Contributions to Cluster API, Metal3, or other open-source Kubernetes infrastructure projects.
NVIDIA’s deep learning platforms have made major impact to various fields is broadly used across leading academic institutions, start-ups, and industry, including the world’s largest Internet companies. We need passionate, hard-working and creative people to help us take on more of these unique opportunities in deep learning cloud solutions. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you.
Skills Required
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience.
- 8+ years of experience building or operating production Kubernetes platforms, network infrastructure, or distributed systems.
- Deep experience with Kubernetes at scale, including cluster lifecycle, upgrades, networking, storage, and recovery.
- Proficiency in at least one general-purpose programming language (such as Go or Python).
- Experience with GitOps, infrastructure as code, CI/CD, and automated production delivery.
- Experience deploying and supporting network automation or telemetry services on Kubernetes.
- Experience with production on-call, incident response, root-cause analysis, and driving corrective actions to completion.
- Strong knowledge of IP routing, data center fabrics, and cloud networking.
- Experience designing and operating large, multi-region Kubernetes fleets, including fleet-wide upgrades and recovery.
- Hands-on experience with Cluster API (CAPI) and Metal3 for bare-metal provisioning, cluster lifecycle, machine remediation, and upgrades.
- Experience building Kubernetes controllers or operators in Go using custom resources and reconciliation patterns.
- Contributions to Cluster API, Metal3, or other open-source Kubernetes infrastructure projects.
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
.jpeg)
