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NVIDIA

Senior Software Engineer Tech Lead, Network System Validation

NVIDIA is hiring a Senior Software Engineer Tech Lead, Network System Validation. Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • On Level's scale, this software engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include C, Python and Nccl.
  • Level classifies it as a senior role.
  • Level lists 2,700+ other open roles at NVIDIA.

AI in this role

Lead the validation of advanced high-speed networking solutions across complex, large-scale AI cluster environments.

CPythonNcclRoceRdma
network-validationsystem-validationperformance-analysisai-clustersdebugging

NVIDIA is shaping the next era of computing, where AI, accelerated computing, and high-speed networking come together to power the world’s most advanced AI systems. Within NVIDIA, the Networking Business Unit (NBU) builds the high-speed interconnect technologies — Ethernet, InfiniBand, NVLink, and BlueField DPUs — that connect thousands of GPUs into a single AI supercomputer.

NVIDIA is looking for a Technical Lead to join our Network System Validation group and lead the validation of advanced networking solutions across complex AI cluster environments. This is a deeply hands-on technical leadership role, combining ownership of the validation roadmap with technical mentoring and engineering excellence. You will develop validation methodologies and automation frameworks, while working hands-on on debugging, performance analysis, and cutting-edge AI networking technologies at scale. Join us to help push NVIDIA’s networking technologies to their limits and shape how next-generation AI infrastructure is validated.

What you’ll be doing:

  • Review system and product requirements, design validation methodologies, develop and implement comprehensive test plans, functional and performance, for networking technologies in large-scale AI cluster solutions
  • Develop and maintain benchmarks, automation tools and scripts for test execution, environment setup, log collection, and data analysis.
  • Lead end-to-end investigation of complex issues by reproducing real-world scenarios, analyzing logs, telemetry, packet captures, and system metrics to identify functional issues and performance bottlenecks, triaging problems across the hardware and software stack, and driving them to root cause and resolution
  • Read and understand source code (C/C++/Python) to investigate defects, validate fixes, and improve logging, instrumentation, and debugging capabilities
  • Collaborate deeply with software and hardware development teams to debug networking technologies, including NCCL, RoCE, RDMA, and related software components using targeted experiments and code inspection
  • Profile and research AI training and inference workloads, correlating application behavior with network and system telemetry to identify scalability and performance limitations
  • Document findings, communicate technical results, and continuously improve validation methodologies, automation environments, and engineering processes

What we need to see:

  • B.Sc. / B.A. in Computer Science, Electrical Engineering, or equivalent experience
  • 12+ years of experience in networking, system validation, or related domains
  • Proven experience debugging complex production systems by forming hypotheses, designing experiments, and driving issues to root cause
  • Ability to read, debug, and reason about C/C++ code (Rust or Go a plus)
  • Strong scripting and automation experience using Python, Bash, and/or Ansible
  • Deep understanding of distributed systems: concurrency, consistency models, fault tolerance, and large-scale system performance under stress
  • Ability to drive technical alignment across teams, communicate tradeoffs clearly, and make high-quality architectural decisions at speed
  • Advance AI-driven approaches to test automation: intelligent scenario generation, LLM-augmented root-cause analysis, and autonomous validation pipelines

Ways to stand out from the crowd:

  • Experience with large-scale clusters or distributed systems
  • Familiarity with NVIDIA networking solutions (ConnectX, SpecX, BlueField)
  • Background in performance analysis, Kubernetes, or cloud environments
  • Background in chaos testing, fault injection, or simulation systems

We have some of the most forward-thinking and hardworking people working for us. If you're creative and autonomous, we want to hear from you! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, disability status or any other characteristic protected by law.

How we rate this

Senior Software Engineer Tech Lead, Network System Validation at NVIDIA rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  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.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Network ValidationSystem ValidationPerformance AnalysisAI ClustersDebuggingCPythonNccl

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$167k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. Tell me about a project where network validation was part of your work. What did you do?
  2. Tell me about a project where system validation was part of your work. What did you do?
  3. Tell me about a project where performance analysis was part of your work. What did you do?
  4. Tell me about a project where ai clusters was part of your work. What did you do?
  5. Tell me about a project where debugging was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Network Validation, System Validation, Performance Analysis, AI Clusters, and Debugging. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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