Senior System Software Engineer, Software-Defined Networking

NVIDIA is hiring a Senior System Software Engineer to advance software-defined networking for global GPU cloud infrastructure supporting AI workloads, cloud gaming, content delivery, and other accelerated services. The role involves designing, building, qualifying, and operating secure programmable networking systems, while leading technical decisions and production improvements in collaboration with engineering, architecture, and partner teams.

Responsibilities:

• Collaborate with engineers and architects to define, review, and evolve multi-tenant control-plane and data-plane architecture using Open vSwitch, OVN, OpenFlow, and overlay network technologies
• Demonstrate technical leadership and mentorship through design and code reviews, implementation guidance, production-readiness decisions, and improvements to engineering quality
• Develop and review production software for Kubernetes networking, network plugins, distributed control planes, Linux host networking, virtual-machine networking, and network automation
• Translate product and infrastructure requirements into secure orchestration services, APIs, component boundaries, state models, compatibility strategies, and delivery plans while driving shared decisions
• Drive Open vSwitch and OVN integration across flow behavior, configuration, lifecycle management, upgrades, interoperability, performance, failure recovery, and large-scale production operation
• Build and implement automated unit, integration, system, performance, scale, and upgrade tests connected to continuous integration, deployment, and release-qualification workflows
• Share the team’s on-call rotation and lead networking escalations with partner teams. Use packet captures, SDN state, telemetry, profiling, controlled experiments, and source debugging to resolve incidents and prevent recurrence
• Define and improve reliability, performance, security, and resource-efficiency objectives while engineering actionable monitoring, telemetry, tracing, and service-level visibility for production networks

Requirements:

• BS or MS in Computer Science, Computer Engineering, or a related field, or equivalent experience
• 12+ years of proven experience designing, implementing, testing, and maintaining production software in both C and Go, with Bash and Python used for test, diagnostic, build, or operational automation
• Concrete experience developing, integrating, and solving issues in Open vSwitch and OVN, including OpenFlow and control-plane-to-data-plane behavior
• Production Kubernetes networking experience, including container network interfaces, network policy, node and pod traffic paths, network-plugins, upgrades, and failure modes
• Strong Linux networking fundamentals and practical understanding of IP, TCP, UDP, routing, switching, overlay networks, tunneling, network namespaces, and network policy
• Experience architecting distributed systems with secure service APIs, state management, consistency, scalability, compatibility, and failure handling
• Experience handling the production lifecycle through automated testing, CI/CD, deployments, upgrades, observability, and performance analysis
• Experience supporting production services through a shared on-call rotation and coordinating incident response through evidence from flows, logs, metrics, traces, profiles, experiments, and source-level debugging
• Collaborative architecture and technical leadership through written designs, consequential decisions, cross-team work, critical reviews, mentoring, and delivery of significant systems through production operation
• Contributions to Open vSwitch, OVN, OVN-Kubernetes, Kubernetes networking, or another relevant open-source project
• Experience with large-scale cloud and accelerated virtualization systems, including SR-IOV, RDMA, SmartNICs, data processing units, network function virtualization, KVM/QEMU, or container runtimes
• Experience building secure, high-performance gRPC or REST services using transport security and strong authentication
• Applied use of agentic AI and AI-assisted software-developmenttooling, including coding agents, reusable skills, or Model Context Protocol integrations