NVIDIA is looking for a talented Software Engineer to join the System Production Engineering group. You will be part of a growing team building the automation frameworks and tooling that validate security on NVIDIA NICs, Smart NICs/DPUs, and Network Switches before they ship. You will work hands-on alongside the team lead, co-developing shared codebases and taking full ownership of standalone modules when needed.
This is a software engineering role first. Your primary language is Python, your primary output is automation frameworks and production tooling — not firmware, not embedded code, not C/C++ feature development. The security domain is the context you'll operate in; it is not a prerequisite. If you code every day, think in abstractions and systems, and raise the quality bar around you — we want to talk.
What you’ll be doing:
Design and own Python automation frameworks and tooling that validate security properties of NVIDIA networking products — from architecture through CI/CD integration
Design, develop and maintain Python-based test automation frameworks and test suites for NVIDIA networking products (NICs, DPUs, switches) — including building test infrastructure from scratch
Own the full lifecycle of automation modules: design, implementation, debugging, CI/CD integration, and production maintenance — end-to-end, with no handoffs
Collaborate with hardware and security architects — translating specs and vendor APIs into clean Python abstractions without needing deep hardware engineering expertise
Collaborate on shared codebases using AI-assisted development tools as a core part of your daily workflow — this is how we work, and you will be expected to hit the ground running with it
Be data-oriented — able to perform analysis on code quality, coverage, and production metrics, and translate findings into clear, data-based decisions and recommendations
What we need to see:
BA/BSc in Computer Science, Computer Engineering or Electrical Engineering (or equivalent)
5+ years of software development experience with hands-on Python — specifically writing automation frameworks, scripts, or tooling in Python, not just application-level development
Strong software design fundamentals: you think in abstractions, interfaces, and design patterns — not scripts. Object-oriented design is natural to you, not something you look up
End-to-end ownership: demonstrable experience owning a Python automation project from design through execution, reporting, and CI/CD integration. Be prepared to share concrete examples or code during the interview process
Proven AI collaboration: you must demonstrate that working with AI-assisted development tools (e.g. GitHub Copilot, Cursor, Claude, or similar) is already part of your development practice — not something you are exploring
Module ownership: ability to independently own and deliver standalone software modules while also working fluidly as part of a collaborative team
OS proficiency: proficient in Windows and Linux operating systems, including command-line debugging and scripting
Execution under pressure: ability to drive projects to completion under schedule pressure and across multiple workstreams simultaneously
Excellent verbal and written communication in both Hebrew and English
Ways to stand out from the crowd:
Automation at scale in production: you have shipped and maintained automation frameworks in real production environments, under schedule pressure — not just in controlled lab or side-project settings
You live and breathe AI-assisted development: Vibe Coding is your natural mode of work; you don't just use AI tools occasionally, you actively seek them out, integrate them into your workflow, and can demonstrate the productivity gains they bring
Security domain curiosity: you don't need hardware security expertise coming in, but you're intellectually curious about new technical domains and ramp up quickly on specs, vendor APIs, and security concepts when needed
System-level thinking: you understand the full stack from the code you write to the infrastructure it runs on — even if you don't live in the hardware layer
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet 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.
Skills Required
- BA/BSc in Computer Science, Computer Engineering or Electrical Engineering (or equivalent)
- 5+ years of software development experience with hands-on Python
- Strong software design fundamentals including abstractions and design patterns
- Demonstrable experience owning Python automation projects through design and execution
- Experience with AI-assisted development tools
- Proficient in Windows and Linux operating systems
- Excellent verbal and written communication in Hebrew and English
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”








