Senior AI Systems Engineer

NVIDIA is hiring a Senior AI Systems Engineer. Level rates it ; you can apply on NVIDIA.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
The posting mentions RAG and AI agents among its tools and skills.
Level classes it as a senior role.
NVIDIA has 2,600+ other open roles on Level.

AI in this role

ragai-agents

NVIDIA is looking for a talented AI Solutions Engineer to join our innovative AI team. The team develops advanced AI platforms and applications including agentic workflows, Retrieval-Augmented Generation (RAG) systems, Large Language Model (LLM) based solutions, AI agents, MCPs, and more. You will have the opportunity to shape how AI transforms our products and internal processes worldwide. Your responsibilities will include implementing state-of-the-art AI technologies, developing all aspects of the project – AI, code, data preparation, evaluation, and deployment. We are looking for a motivated teammate who thrives on solving complex problems with AI and continuously explores emerging techniques in this rapidly evolving field.

What you'll be doing:

Design and implement Agentic platforms and workflows to simplify the agentic experience across the company.
End-to-end solutions Implementation to increase the organization quality and productivity.
Develop AI solutions that integrate seamlessly with existing products and workflows
Build evaluation frameworks to measure and improve AI system performance
Collaborate with cross-functional teams to identify and implement AI opportunities
Collect and prepare data from multiple large scale sources for AI training and inference

What we need to see:

B.Sc. (or equivalent experience) in Computer Science, AI, Machine Learning or related field
6+ years of experience in software development and building production-grade software systems.
1+ years of experience building LLM-based solutions, AI agents, and AI workflows.
Proficiency in Python
Strong understanding of modern AI concepts and practical applications
Proficiency in Python

Ways to stand out from the crowd:

Strong understanding of modern Machine Learning domains, known algorithms, architectures and techniques
Experience developing large scale software, including in a micro services architecture
Experience with vector databases, embedding technologies and RAG systems
Experience developing AI agent architectures and orchestration systems

How we rate this

Senior AI Systems Engineer at NVIDIA rates 94 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 AI Systems Engineer is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Israel, Yokneam.
The job was posted on September 20, 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 agents

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 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 and AI agents. 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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