Senior Software Engineer, AI Networking

NVIDIA NVIDIA · Semiconductors · Austin, TX +1

Senior Software Engineer role focused on AI networking products, specifically BlueField DPU and ConnectX. The role involves architecting, designing, and developing hardware-accelerated software solutions, leading technical engagements with hyperscalers, and driving performance/reliability improvements. Requires deep expertise in networking protocols, distributed systems, and low-level software development.

What you'd actually do

  1. Establish yourself as a technical specialist in AI networking products, specifically the BlueField DPU and ConnectX product lines. Architect, design, and develop innovative, scalable, and high-performance hardware-accelerated software solutions.
  2. Lead deep technical engagements with hyperscalers, involving design-in, coding, bring-up, performance tuning, failure analysis, and production hardening.
  3. Partner with internal engineering, product, and architecture teams to transform customer needs into product features, reference architectures, tooling, and guidelines.
  4. Drive performance, reliability, and debuggability improvements across customer stacks and translate findings into actionable product, firmware, and software roadmap items.

Skills

Required

  • Bachelor's, Master's or PhD in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering or a related science degree (or equivalent experience)
  • 8+ years of relevant industry experience, including technical leadership across complex systems.
  • Deep knowledge of networking protocols and distributed systems, with a strong understanding of RoCE/InfiniBand, L1–L4 fundamentals, and performance/latency tradeoffs.
  • Proven low-level software expertise with proficiency in C/C++ and comfort debugging across firmware, driver, OS, and application.
  • Demonstrated experience in high-performance networking and system-level debugging, including packet drops, retransmissions, congestion, QoS, ordering, and buffer management.
  • Excellent interpersonal skills, with the ability to clearly explain complex topics to engineers, PMs, and customer collaborators, and align cross-organizational teams toward a decision.
  • Result driven and comfortable multitasking in a dynamic environment with shifting priorities and changing requirements

Nice to have

  • Prior experience in customer-facing technical leadership at hyperscalers/CSPs.
  • Hands-on expertise with RDMA verbs, DPDK, DOCA, NCCL, CUDA-aware networking, congestion control, and performance tuning at scale.
  • Experience building internal tools, telemetry, and automation that improve triage speed and operational excellence.
  • Experience leading multi-team initiatives across geo/time zones, with clear examples of influence without authority as well as eager and proactive in bringing to bear AI-powered tools to accelerate debugging, documentation, and day-to-day engineering efficiency while maintaining strong engineering judgment.

What the JD emphasized

  • technical leadership
  • deep expertise
  • high-performance networking
  • low-level software expertise
  • system-level debugging
  • customer-facing technical leadership
  • performance tuning at scale
  • AI-powered tools