Senior Software Engineer, AI Infrastructure Solutions

NVIDIA is hiring a Senior Software Engineer, AI Infrastructure Solutions in Santa Clara, United States. It pays $152k-$242k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include Python, C and RAG.
Level classifies it as a senior role.
Level lists 2,700+ other open roles at NVIDIA.
The role was posted within the past week.

AI in this role

Build agentic AI solutions and scalable AI infrastructure to automate GPU testing, validation, and debugging workflows.

pythonc

ragai-agentsml-opsai-automationai-evaluationagentic-aiai-infrastructurelarge-language-modelsautomation

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 an inclusive, 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’s Modular Diagnostics team and lead AI-powered innovation. Our team develops key diagnostic applications and infrastructure to test every NVIDIA GPU. This ensures flawless performance before launch. As part of the Senior Software Engineer, AI Infrastructure Solutions team you will build intelligent automation. This automation speeds up critical engineering workflows and improves GPU validation speed and quality.

What you'll be doing:

Build and deliver agentic AI solutions—autonomous systems that reason, plan, and take actions. These automate silicon bring-up, test and validation frameworks, debugging, and engineering workflows to speed up GPU launches.
Build scalable AI infrastructure, services, APIs, and reusable platforms that enable teams across NVIDIA to develop and deploy AI-powered applications.
Integrate AI agents with engineering tools, knowledge bases, data platforms, and existing business processes to build end-to-end intelligent workflows.
Partner with multi-functional teams across Modular Diagnostics and adjacent organizations to identify high-impact use cases, define requirements, develop prototypes, and deploy production-ready solutions.
Establish evaluation, observability, security, and reliability practices for AI systems to ensure solutions perform at scale and meet enterprise standards.
Drive projects from concept through adoption, measure their impact against clear success criteria, and continuously improve their efficiency.

What we need to see:

BS or MS degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
5+ years delivering production software, infrastructure, platform, or AI solutions.
Strong programming skills in Python and C/C++.
Track record of building applications with large language models, AI agents, retrieval-augmented generation, tool use, or workflow orchestration.
Demonstrated ability to build scalable services, APIs, data pipelines, and production software infrastructure.
Strong problem-solving, debugging, and system-design skills with a history of shipping reliable systems.
Effective collaboration across technical and business teams, with clear communication and the ability to drive solutions from idea to production.

Ways to stand out from the crowd:

Background in GPU computing, CUDA, GPU architecture, or silicon bring-up processes.
Familiarity with engineering diagnostics, hardware development workflows, or systems software.
Hands-on work with MLOps, model evaluation frameworks, AI observability tools, or production AI monitoring.
Contributions to open-source AI/ML projects or developer tools.
Prior work building internal developer platforms or engineering efficiency tooling.

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

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 26, 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

Senior Software Engineer, AI Infrastructure Solutions at NVIDIA rates 90 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. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Software Engineer, AI Infrastructure Solutions is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $152k-$242k a year.
The role is based in US, CA, Santa Clara.
The job was posted on October 22, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsML OpsAI AutomationAI EvaluationAgentic AIAI InfrastructureLarge Language Models

Also common in software engineer jobs at this level

AWS Machine learning Kubernetes Java Generative AI TypeScript

Pay

This job starts at: $152k
Typical software engineer job: $168k

This posting starts 10% below the typical software engineer job. See software engineer jobs

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?
How do you monitor a model once it's live, and how do you know it needs retraining?
Tell me about a workflow you automated with AI tools, end to end.
How do you decide that one model's output is better than another's for a given task?

Adapt your resume

List these exact terms on your resume: RAG, AI agents, ML Ops, AI Automation, and AI Evaluation. 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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