We are seeking a highly skilled Senior Network Automation Architect to design, implement, and oversee end-to-end automation frameworks for provisioning Baremetal and Kubernetes clusters across hybrid and multi-cloud environments. This role blends deep networking expertise with infrastructure-as-code principles, enabling rapid, reliable, and secure deployment of Kubernetes clusters at scale.
The successful candidate will work closely with SREs, platform engineers, network engineers, and Tooling teams to automate cluster lifecycle management, integrate provisioning workflows with CI/CD pipelines, and ensure observability, resilience, and compliance across all automation systems.
What you’ll be doing:
Design scalable, secure, and repeatable automation for Kubernetes cluster provisioning and network configuration across multi-cloud, on-prem, and hybrid environments.
Build Infrastructure-as-Code templates, automation pipelines, and CI/CD integrations to streamline provisioning and connectivity.
Automate networking integrations including CNI plugins, service meshes, load balancers, and ingress controllers.
Implement policies, firewalling, routing, and self-service provisioning through API-driven workflows.
Deliver observability with monitoring, logging, alerting, and self-healing workflows to improve resilience and performance.
Act as the technical authority for network automation, mentoring teams and driving cross-functional automation maturity.
What we need to see:
Deep knowledge of Kubernetes networking (CNI, services, ingress, eBPF) and service meshes (Istio, Linkerd, Consul).
Strong background in network security, firewalling, routing, and containerized environments.
Hands-on experience with IaC and automation tools (Terraform, Ansible, Pulumi), GitOps tooling (ArgoCD, Flux), and CI/CD systems.
Proficiency in Python, Go, or Bash, with experience building API-driven integrations (REST, gRPC).
Familiarity with Kubernetes lifecycle management and provisioning tools (CAPI, kubeadm, kops, Rancher, OpenShift, bare metal).
Experience with observability and tracing stacks (Prometheus, Grafana, ELK/EFK, Jaeger, OpenTelemetry).
8+ years in network engineering and automation development. 3+ years of experience with Kubernetes platform engineering.
Bachelor's degree or equivalent experience.
Ways to stand out from the crowd:
Proven track record of crafting and delivering automated provisioning solutions at scale.
Experience with multi-cloud networking (AWS VPC, Azure VNet, GCP VPC)m
Excellent architecture documentation and interpersonal skills. Ability to lead cross-functional technical initiatives.
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.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5.You will also be eligible for equity and benefits.
Top Skills
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.”
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