NVIDIA

Software Engineer - AI Solutions

In short

Hands-on software engineering role building AI agents and tools that speed up development, verification, and debugging of Linux networking drivers at NVIDIA. The team works across the full software development lifecycle, connecting AI solutions to production engineering systems. Requires 3+ years of software development experience, strong Python skills, and hands-on experience with LLM-based applications like agents, tool use, or RAG. This is an onsite, full-time senior position in Israel.

About the Role
We are looking for a talented Software Engineer to join the AI Solutions team in NVIDIA's Linux Networking Drivers organization. Our mission is to bring AI into every stage of how we build software: design, development, verification, debugging, and release. We build AI agents and tools that make our engineers faster and our drivers better. This is a hands-on development role in a field that changes every few months. You will turn new AI capabilities into solutions that engineers use every day, and you will help decide where AI can make the biggest difference next. If you are passionate about AI and want to apply it to a complex, real engineering domain, we want to hear from you.
What You'll Be Doing
•Design, develop, and deploy AI agents and tools for the software development lifecycle.
•Work with developers and verification engineers to understand their workflows and find where AI can help most.
•Measure the quality of AI solutions and improve them based on data.
•Connect AI solutions to engineering systems and data, and run them reliably in production.
•Follow the fast progress of AI models and tools, and bring the best of them into the team's work.
What We Need to See
•B.Sc. in Computer Science, Software Engineering, or a related field, or equivalent experience.
•3+ years of software development experience.
•Strong Python skills. You build well-structured systems, not just scripts.
•Hands-on experience building applications with LLMs, such as agents, tool use, or RAG.
•Strong problem-solving skills and the ability to take a feature from idea to production.
•Excellent verbal and written English. We are a multi-language team that works across sites and time zones.
Ways to Stand Out
•Experience evaluating the quality of LLM-based systems.
•Knowledge of the Linux kernel, networking, or device drivers.
•Experience with test automation or verification.
•Full stack or DevOps experience.
•A track record of AI tools that real users adopted.

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