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Senior Site Reliability Engineer - Kubernetes Platform

NVIDIA· Engineer, Sys SW
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Santa Clara, CA, Durham, NC, Austin, TX$184k - $287.5kFull-timePosted 7mo ago

About the role

Senior SRE responsible for owning and scaling NVIDIA's Kubernetes platform for large-scale edge and on-prem/cloud workloads, integrating multi-cluster lifecycle, IaC/GitOps, observability, incident response, and collaboration with EDA, storage, and network teams.

Responsibilities

  • Own Kubernetes clusters end-to-end - plan, deliver, upgrade, day-2 operations, and decommission - across on-prem datacenters and managed cloud Kubernetes (e.g. EKS, GKE, RKE, Red Hat OpenShift, etc).
  • Define and implement the multi-cluster lifecycle strategy: version skew policy, patch cadence, node image pipelines, controlled rollouts, and safe upgrade mechanics for clusters that can't simply be drained on demand.
  • Treat on-prem and CSP Kubernetes as one platform with consistent APIs, policy, and observability - not as two disconnected worlds.
  • Drive everything through Infrastructure-as-Code, GitOps, and declarative config; manual cluster changes should be an anomaly worth investigating.
  • Design for failure: explicit fault domains, blast-radius containment between clusters and tenants, progressive delivery, and disciplined change control.
  • Build end-to-end observability (metrics, logs, traces, events) and push toward data-driven and auto-healing operations that materially reduce human intervention.
  • Participate in on-call, lead incident response, drive root cause analysis, and publish high-quality RCAs that actually change the system.
  • Partner with EDA engineering, storage, and network teams to land changes cleanly in a fast-moving environment.
  • Engage and partner with data center operations to forecast, design and implement accurate on-prem and cloud deployments to meet architectural needs.
  • Interface directly with internal EDA tenants/engineering teams to design and implement operational improvements to increase productivity and provide faster and more reliable outcomes; partner with the infrastructure services team to architect supporting capabilities for intelligent workload routing, observability, dynamic scaling and resource governance.

Qualifications

  • Bachelor's degree in Computer Science or related technical field (or equivalent experience) with 8+ years building and supporting critical production services.
  • Deep, hands-on Kubernetes operations experience - debugging etcd, kubelet, CNI, CSI, scheduler behavior, API server load, container runtime, and control-plane degradation under production pressure.
  • Production experience with CSP-managed Kubernetes — upgrade model, networking and IAM integration, node group lifecycle, and managed abstractions.
  • Production experience operating self-managed Kubernetes on-premises across multiple datacenters — cluster bring-up, bare-metal and GPU node lifecycle, multi-site topology, and stack ownership implications.
  • Strong command of CI/CD and Infrastructure-as-Code (Terraform, Ansible, Helm, Kustomize, Argo CD/Flux or equivalents).
  • Experience building large-scale infrastructure platforms for automated host lifecycle management, fleet reliability and auto-healing, end-to-end observability, or data-driven operations (AIOps/ML-driven signals).
  • Proficiency with monitoring, metrics, and log collection tooling (Prometheus, Grafana, OpenTelemetry, Loki/ELK, containerd, etc.).
  • 5+ years of coding/scripting focusing on automation and operational management at scale in at least two languages (Go, Python, Perl, Ruby); Go strongly preferred for controller/operator work.
  • Track record mentoring engineers and influencing technical direction through design reviews and architecture documents.

Skills

Required:Kubernetes operationsInfrastructure as Code (IaC)CI/CDObservabilityProgramming/Scripting

Benefits

  • Equity
  • Benefits are described on NVIDIA's benefits page (link provided in job posting)
Last updated Oct 23, 2026. Interested? Apply on the company site.

About NVIDIA

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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