Senior System Software Engineer, Software Defined Networking

NVIDIA • Artificial Intelligence • Information Technology • Bachelor's Degree • Python • Bash • 1 hour ago
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Salary
≈ $29k – $72k per year (Estimated)
Location
Remote/Hybrid (Bengaluru, India)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
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NVIDIA

NVIDIA is an American technology company founded in 1993 that invented the graphics processing unit and has become the dominant supplier of accelerated computing platforms for artificial intelligence. Its portfolio spans data centre GPUs and systems built on the Hopper and Blackwell architectures, GeForce consumer graphics, automotive and robotics platforms, high-speed networking acquired with Mellanox, and the CUDA software stack that binds the ecosystem together. Headquartered in Santa Clara, California, the company sells to cloud providers, enterprises, research institutions and gamers worldwide and is one of the most valuable listed businesses on the Nasdaq.
nvidia.com • HQ: Santa Clara, United States • Autonomous Driving • Information Technology • Artificial Intelligence • Computer Components • AI Infrastructure • AI Chips & Accelerators • Semiconductors • 5000+ employees • Est. 1993

We are looking for a Senior 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; Drive reliability through incident management, resource monitoring, and performance tuning

  • 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

  • 5+ 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)

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