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Cloud Foundations Reliability (CFR) is part of NVIDIA s Global Network Infrastructure (GNI) organization. We deploy, integrate, and operate the Kubernetes-based platform and shared services used to provision, monitor, and operate NVIDIA s global network across data centers, colocation facilities, and cloud environments. The team owns the architecture and lifecycle of this platform, including cluster provisioning and upgrades, GitOps delivery, observability, capacity, and service enablement. We build software and automation to standardize how network platforms and services are deployed, scaled, and managed across environments. 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: - Solid 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 autonomousDo you love a challengeIf so, we want to hear from you. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.