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

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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