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NVIDIA

Designs the chips and software that power AI

Network Solution Verification Engineer

Test Automation EngineeringConfirmed live in the last 24 hours
Full-timeRa'anana, IsraelNo salary listedIn-person

About the Job

Requirements

  • A B.Sc. degree or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field.
  • At least 3 years of hands-on experience as a software developer.
  • Strong proficiency in Python for test automation, tooling development, and pipeline implementation.
  • Hands-on experience with network simulation or emulation tools such as Containerlab, GNS3, SONiC testbeds, or equivalent platforms.
  • Experience designing and building simulation agents or traffic generators that mimic real-world networking behavior at scale.
  • Experience with agentic AI frameworks and large language model-based automation such as LangChain, LangGraph, AutoGen, or similar, and practical ability to apply them to validation and test generation workflows.
  • Command of regression analysis methodologies, including triaging and classifying results and extracting actionable conclusions from large-scale test result datasets.
  • Ability to work in a fast-paced, cross-functional, multi-timezone engineering environment, with strong verbal and written communication skills.

Responsibilities

  • Design and implement end-to-end validation frameworks for customer-facing networking solutions at scale, leveraging a dedicated end-to-end simulation cluster environment.
  • Write, maintain, and extend automated test suites and regression pipelines for networking protocols and large-scale simulation runs to ensure repeatable, high-confidence validation outcomes.
  • Perform regression analysis on simulation results, identify failure trends, isolate root causes, and deliver actionable findings to architecture and design teams.
  • Develop agentic AI flows to autonomously perform regression analysis, detect coverage gaps, generate test cases, and implement validation code, learning from simulation results and product changes to accelerate coverage.
  • Integrate validation pipelines into continuous integration and continuous delivery workflows for continuous automated regression at scale, working with DevOps and platform teams.
  • Collaborate with Design, Architecture, and NCS teams to understand solution requirements, translate them into simulation scenarios, and provide early-cycle quality feedback that influences product direction.
  • Analyze customer-reported networking issues, map them to simulation coverage gaps, and build targeted test cases that prevent regression.
  • Explore simulation technologies, agentic frameworks, and networking standards to improve the team's validation methodology.

Desired Qualifications

  • Hands-on experience validating data center networking solutions or hyperscale network environments, including spine-leaf, fat-tree, or Clos topologies.
  • Familiarity with NVIDIA networking products, including BlueField DPUs, ConnectX NICs, Spectrum switches, or the DOCA software stack.
  • Deep understanding of networking protocols and architectures, including BGP, EVPN, VXLAN, RDMA/RoCE, Ethernet, IP routing, and L2/L3 switching.
  • Hands-on experience building agentic pipelines for automated test generation, result triage, or validation code synthesis, including prompt engineering and tool-use patterns for large language model agents.
  • Prior exposure to customer-facing solution validation or translating customer deployment scenarios into structured simulation test cases.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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