Systems Software Engineer - AI and Cloud

AI in this role

vllm

ragai-agents

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

Join NVIDIA, where we are pushing the boundaries of what's possible in AI and cloud computing. As a versatile System Software Engineer - AI and Cloud, you will be part of a team of dedicated professionals that thrives on innovation and collaboration. Located in the heart of Silicon Valley, you will have the opportunity to work on groundbreaking projects that craft the future of technology. This role offers an outstanding chance to engage with advanced AI models and cloud-native architectures, making significant contributions to NVIDIA’s versatile products and technologies.

What you'll be doing:

Evaluate cloud-native, full-stack applications using microservices architecture to power AI use cases, bringing to bear NVIDIA frameworks, SDKs, and microservices.
Design and implement agentic workflows with advanced techniques like Retrieval-Augmented Generation (RAG) and the latest AI models.
Evaluate user experiences and analyze the technical performance of AI solutions, compiling findings into comprehensive reports. Offer practical suggestions for product improvement to senior executives and engineering management.
Engage with various teams across NVIDIA such as product, marketing, hardware, software engineering, and QA to improve NVIDIA's product offerings.
Develop developer-focused content, including detailed tutorials and code samples, to demonstrate the latest features in NVIDIA’s tools and libraries.
Write technical whitepapers and product briefs, and run technical demos of our products at prominent industry conferences.

What we need to see:

A Bachelor’s or Master’s in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering or a related degree (or equivalent experience)
3+ years of experience.
Proficiency in Python and JavaScript for programming and debugging, with a strong foundation in data structures, algorithms, and software design principles.
Basic familiarity with C++ programming and its application in high-performance computing environments.
Experience in crafting cloud-native systems optimized for Kubernetes deployment, using inference frameworks such as vLLM and NVIDIA Triton Inference Server.
A solid understanding of API design principles for building scalable, production-ready inference systems.

Ways to stand out from the crowd:

Advanced knowledge of LLMs, modern AI software architecture, and cloud APIs.
Contributions to public-facing technical content and open-source projects.
Expertise in deploying LLM inference frameworks like Triton Inference Server, vLLM, or TensorRT, including on Kubernetes or edge devices to improve performance.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 5, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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, veteran status, disability status or any other characteristic protected by law.

How we rate this

Systems Software Engineer - AI and Cloud at NVIDIA rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGAI AgentsvLLM

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
What are the limits of vLLM that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: RAG, AI Agents, and vLLM. 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.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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