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
Skills Required
- Bachelor of Science degree or equivalent experience in Computer Science, Artificial Intelligence, Machine Learning, or a 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
- Strong understanding of modern machine learning domains, algorithms, architectures, and techniques
- Experience developing large-scale software, including microservices architectures
- Experience with vector databases, embedding technologies, and RAG systems
- Experience developing AI agent architectures and orchestration systems
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
