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NVIDIA

Principal Engineer, Software Defined Networking

NVIDIA is hiring a Principal Engineer, Software Defined Networking for a remote role open to applicants in United Kingdom. Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Level rates this role Little AI ●○○○: aI is not part of the work.
  • This is listed as a remote role.
  • Level classes it as a lead role.
  • NVIDIA has 2,700+ other open roles on Level.
  • Posted in the last few days.

AI in this role

We are looking for a Principal System Software Engineer, Software Defined Networking to design, build, and operate highly performant and scalable SDN solutions for NVIDIA's AI Clouds hosting GPU-accelerated workloads — including hyperscale multi-node training, inference, cloud gaming, and cloud functions. This role spans the full lifecycle of our SDN stack — from designing and developing new control and data plane software to ensuring operational excellence in production through reliability engineering, CI/CD, observability, and incident response.


What you'll be doing:

  • Design and develop next-generation multi-tenant cloud SDN control and data plane software (OVS, OVN, OpenFlow)
  • Build Infrastructure-as-a-Service virtual network orchestration and services using gRPC and REST to support tenant workload security and performance SLAs for BMaaS, VMaaS, and Kubernetes
  • Drive upstream contributions to OVN-Kubernetes and related open-source projects
  • Develop software for network observability — monitoring, telemetry, intelligent metering, and performance analysis
  • Operate and support OVS-OVN based SDN solutions in large-scale NVIDIA AI Cloud environments
  • Own end-to-end observability for the SDN stack — build and maintain monitoring, alerting, distributed tracing, and dashboarding to ensure real-time insight into network health, performance, and tenant SLAs
  • Design, enhance, and maintain CI/CD pipelines (GitLab) across Linux host networking, OVS, OVN, and Kubernetes CNIs
  • Implement GitOps approaches or related experience for secure, seamless integration with cloud infrastructure
  • Collaborate with SRE, DevOps, and network engineering teams on production readiness and operational tooling

What we need to see:

  • BS/MS in Computer Science or related technical field, or a comparable blend of education and relevant experience
  • 15+ years of proven experience in software development for large-scale distributed environments
  • Expert-level knowledge of OVN, OVS, OpenFlow, and modern network protocols
  • Strong programming skills in C and Go; advanced scripting in Bash and Python
  • Deep knowledge of Kubernetes, practical experience deploying and supporting CNIs (OVN-Kubernetes)
  • Hands-on experience with Infrastructure-as-Code and deployment tools (Ansible, Terraform, ArgoCD, Flux)
  • Experience designing and operating complex, multi-stage CI/CD pipelines
  • Hands-on experience developing secure, high-performance services using gRPC and REST with TLS and strong authentication
  • Strong knowledge of datacenter routing, switching, and Linux host/VM networking

Ways to stand out from the crowd:

  • Contributions to open-source projects (especially OVS, OVN, OVN-Kubernetes, or other Kubernetes networking projects)
  • Experience with hardware acceleration (GPU, DPU or equivalent experience) for networking 
  • Practical experience with major cloud providers (AWS, Azure, GCP) and hybrid/multi-cloud deployments
  • SRE/DevOps top-level expertise — on-call, incident management, operations focused on service reliability targets, production ownership
  • Experience with observability platforms and tools (Prometheus, Grafana, Jaeger, OpenTelemetry, ELK)

How we rate this

Principal Engineer, Software Defined Networking at NVIDIA rates 27 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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