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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, AI Networking - **Company:** NVIDIA Corporation - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $184,000.0 - $287,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, C++ (Programming Language), Nvidia CUDA, Computer Engineering, Network Congestion, Software Debugging, Distributed Systems, Firmware, InfiniBand, Network Protocols, Performance Tuning, Remote Direct Memory Access, Software Engineering, Software Systems, System Programming, Application Enhancement Tool, Information Technology - **Published:** August 28, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-WA-Seattle/Senior-Software-Engineer--AI-Networking_JR2021027-1 ## About the Role * A 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 Ways to stand out from the crowd: * 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. ## Description * 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. * Lead deep technical engagements with hyperscalers, involving design-in, coding, bring-up, performance tuning, failure analysis, and production hardening. * Partner with internal engineering, product, and architecture teams to transform customer needs into product features, reference architectures, tooling, and guidelines. * Drive performance, reliability, and debuggability improvements across customer stacks and translate findings into actionable product, firmware, and software roadmap items. ## Related Videos - [The Gashlycrumb Tinies of AI Networking You Must Know (or Languish!)](https://www.wearedevelopers.com/videos/2067-the-gashlycrumb-tinies-of-ai-networking-you-must-know-or-languish) - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Playing Pong on a shoulder press machine](https://www.wearedevelopers.com/videos/100140-playing-pong-on-a-shoulder-press-machine) - [Building the Nervous System of AI - Michael Kagan (NVIDIA)](https://www.wearedevelopers.com/videos/2133-building-the-nervous-system-of-ai-michael-kagan-nvidia) - [A Deep Dive on How To Leverage the NVIDIA GB200 for Ultra-Fast Training and Inference on Kubernetes](https://www.wearedevelopers.com/videos/1625-a-deep-dive-on-how-to-leverage-the-nvidia-gb200-for-ultra-fast-training-and-inference-on-kubernetes) - [The weekly developer show: Boosting Python with CUDA, CSS Updates & Navigating New Tech Stacks](https://www.wearedevelopers.com/videos/1293-the-weekly-developer-show-boosting-python-with-cuda-css-updates-navigating-new-tech-stacks) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)