Senior Data and AI Solutions Engineer
NVIDIA is hiring a Senior Data and AI Solutions Engineer. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Python, SQL and RAG Pipelines 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
Build production-grade agentic AI solutions, data infrastructure, and automated workflows to drive engineering productivity.
NVIDIA is a world leader in computer graphics, artificial intelligence, and accelerated computing. For over 30 years, NVIDIA has been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the world's hardest problems.
NVIDIA’s Networking System Product Engineering organization is looking for a Senior Data & AI Solutions Engineer - high-agency, self-directed Data & AI Solutions Engineer to partner with engineering teams and transform data, BI, automation and agentic AI into measurable engineering productivity gains.
What you’ll be doing
- Work closely with engineers, managers, and cross-functional teams to understand complex engineering domains, identify bottlenecks, and build practical solutions that improve decision-making, execution speed, and operational quality.
- Develop and deliver production-grade tools, automated workflows, and agentic AI solutions from concept through deployment.
- Run fast, high-quality proof-of-concepts on emerging AI and agentic technologies, and productize successful ones.
- Implement data flywheels that continuously improve quality through telemetry, benchmarking, automated evaluation, and structured feedback loops.
- Collaborate and contribute ideas and code to Product Engineering's evolving data infrastructure.
- Improve data quality, integrity, governance, metric definitions, and usability across engineering domains.
- Train and enable engineers, managers, and stakeholders to use data, BI, and AI tools effectively
What we need to see
- B.Sc or M.Sc in Computer Science, or related field, or equivalent experience.
- 12+ years of proven experience building and deploying production software, data products, internal tools, or engineering productivity platforms and 2+ years of experience building AI-enabled or agentic systems, including tools & skills, RAG pipelines, persistent memory, and evaluation infrastructure.
- Hands-on development experience with Python, full-stack software development, SQL and NoSQL databases, cloud environments, and internal tool development.
- Extensive experience utilizing coding agents for development.
- A proactive, high-agency builder who deciphers complex domains to deliver pragmatic, production-grade AI and data solutions that drive measurable engineering productivity.An adaptable expert who masters the intersection of software engineering and agentic AI, taking full ownership of the lifecycle from messy data debugging to cross-functional leadership.
- Excellent collaboration skills, with the ability to influence cross-functional partners, build positive relationships, and communicate complex concepts clearly to both technical and business audiences.
- Demonstrated commitment to continuous learning and development.
Ways to stand out from the crowd
- Background in product engineering, hardware engineering, networking, semiconductors, or complex engineering organizations
- Evidence of meaningful open-source contributions, including core commits, maintainership, widely adopted libraries, or public technical artifacts demonstrating system-level depth
NVIDIA is widely considered to be one of the technological world’s most desirable employers. We have some of the most brilliant and talented people in the world 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. 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 Data and AI Solutions Engineer at NVIDIA rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● 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?
- Tell me about a project where ai solutions was part of your work. What did you do?
- Tell me about a project where agentic ai was part of your work. What did you do?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where automation was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, AI Solutions, Agentic AI, Data Engineering, and Automation. 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.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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