Senior AI Workflow Engineer
NVIDIA is hiring a Senior AI Workflow Engineer in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this role is Uses AI ●●○○: an ordinary role that requires AI tools.
- The posting mentions RAG, AI agents and fine tuning among its tools and skills.
- Level classes it as a senior role.
- NVIDIA has 2,700+ other open roles on Level.
AI in this role
Today, NVIDIA is 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, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world.
NVIDIA is hiring senior software engineers in its Infrastructure, Planning and Process Team (IPP), to accelerate AI adoption across various engineering workflows within the company. IPP is a global organization within NVIDIA. The group works with various other teams within NVIDIA such as Graphics Processors, Mobile Processors, Deep Learning, Artificial Intelligence and Driverless Cars to cater to their infrastructure and software development workflow needs. As a senior engineer on AI Workflow, you will design and implement tools and software solutions that leverage Large Language Models and agentic AI to automate end to end software engineering workflows and enhance the productivity of engineers across NVIDIA.
What you’ll be doing:
Design and implement AI-driven optimizations within software development workflows to enhance developer productivity, accelerate feedback loops, and improve release reliability.
Experience designing, developing, and deploying AI agents to automate and software development workflows and processes.
Continuously measure and report on the impact of AI interventions, demonstrating improvements in key metrics like cycle time, change failure rate, and mean time to recovery (MTTR).
Create and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures.
Conduct research on emerging technologies to recommend best practices and improvements
What we need to see:
BE (MS preferred) or equivalent experience in EE/CS with 10+ years of work experience.
Well versed with Large Language Mode (LLM), Machine Learning (ML), Agentic AI techniques.
Hands-on experience in using large language models (LLMs) and implementing AI for software engineering workflows.
Hands-on experience on Python/Java/Go with extensive python scripting experience.
Experience in working with SQL/NoSQL database systems such as MySQL, MongoDB or Elasticsearch.
Experience in Full stack development.. Proficient in front-end (e.g., React, Angular, Vue.js, HTML, CSS, JavaScript), back-end (e.g., Node.js, Python/Django/Flask, Ruby on Rails, Java/Spring, .NET) development, database management (SQL/NoSQL), and deployment/hosting (e.g., AWS, Azure, GCP).
Experience with tools for CI/CD setup such as Jenkins, Gitlab CI, Packer, Terraform, Artifactory, Ansible, Chef or similar tools.
Good understanding of distributed systems, understanding of microservice architecture and REST APIs.
Good to have knowledge of build tools like Make, Maven or Ant.
Ability to effectively work across organizational boundaries to enhance alignment and productivity between teams.
Ways to stand out from the crowd:
Proactively track AI tool and technology trends, build insights, and collaborate with development teams early to evangelize AI driven workflows NVIDIA adoption.
We have some of the most forward-thinking and versatile people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. We are building a team that will truly change the world. If you are passionate about new technologies, care about software quality, and want to be part of the future of transportation and AI, I would love for you to join us.
Expertise in leveraging large language models (LLMs) and Agentic AI to automate complex workflows, with knowledge of retrieval-augmented generation(RAG) and fine-tuning LLMs on enterprise data.
Prior development of a large software project using service oriented architecture operating with real time constraints
We have some of the most forward-thinking and versatile people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. We are building a team that will truly change the world. If you are passionate about new technologies, care about software quality, and want to be part of the future of transportation and AI, we would love for you to join us.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 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 AI Workflow Engineer at NVIDIA rates 50 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● 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.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
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?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- This role expects you to use AI tools as part of the job. Which ones have you used, and for what?
- Tell me about a time an AI tool got something wrong. How did you catch it?
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, and Fine-tuning. 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.
- Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.
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