6 days ago
Base Salary
$152k - $288k/yr
Responsibilities
- Own Kubernetes clusters across on-premises datacenters and managed cloud Kubernetes, from planning and delivery through upgrades, day-two operations, and decommissioning.
- Define multi-cluster lifecycle policies covering version skew, patch cadence, node image pipelines, controlled rollouts, and safe upgrades.
- Unify on-premises and cloud Kubernetes through consistent APIs, policy, and observability.
- Automate infrastructure using Infrastructure-as-Code, GitOps, and declarative configuration.
- Design fault domains, blast-radius containment, progressive delivery, and disciplined change control.
- Build end-to-end metrics, logging, tracing, and event observability with data-driven and auto-healing operations.
- Participate in on-call, lead incident response, conduct root cause analysis, and publish corrective RCAs.
- Partner with EDA engineering, storage, networking, infrastructure services, and data center operations teams.
- Improve workload routing, observability, dynamic scaling, resource governance, and internal engineering productivity.
Requirements
- Bachelor’s degree in Computer Science or a related technical field, or equivalent experience, with 8+ years building and supporting critical production services.
- Deep hands-on production experience operating Kubernetes, including debugging etcd, kubelet, CNI, CSI, scheduler behavior, API server load, container runtime, and control-plane degradation.
- Production experience with managed cloud Kubernetes, including upgrades, networking, IAM integration, node group lifecycle, and platform limitations.
- Production experience operating self-managed Kubernetes on-premises across multiple datacenters, including bare-metal and GPU node lifecycle management.
- Strong experience with CI/CD, Infrastructure-as-Code, Terraform, Ansible, Helm, Kustomize, and Argo CD or Flux.
- Experience building large-scale infrastructure platforms for host lifecycle management, fleet reliability, auto-healing, observability, or data-driven operations.
- Proficiency with Prometheus, Grafana, OpenTelemetry, Loki or ELK, and containerd.
- At least 5 years of coding or scripting for automation and operational management at scale in at least two languages such as Go, Python, Perl, or Ruby; Go is strongly preferred for controller and operator work.
- Experience mentoring engineers and influencing technical direction through design reviews and architecture documents.
- Preferred qualifications include EDA or silicon-design workflow experience, license-constrained compute experience, production Kubernetes controllers or plugins, stateful or GPU workloads, technical publications, and open-source maintenance.
Benefits
- Eligible for equity and benefits.
- Base salary depends on location, experience, and comparable employee pay.
- Applications are accepted at least until October 20, 2026.
- This posting is for an existing vacancy.
Tech Stack
AnsibleArgo CDAWSGoGoogle Cloud PlatformGrafanaHelmKubernetesOpenShiftPerlPrometheusPythonRubyTerraform
Categories
DevOpsSite Reliability
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.