Join NVIDIA as a Senior Solutions Architect, Agentic AI, focusing on the Public Sector. You will architect and deliver advanced generative AI solutions, specializing in Large Language Models (LLMs) and Agentic AI.

This pivotal role requires deep expertise in LLMs, agentic workflows, and RAG-based systems. You will collaborate with customers and internal teams to drive innovation and implement cutting-edge AI strategies.

NVIDIA offers a dynamic environment with competitive compensation and benefits, making it a premier destination for passionate and innovative engineers. Be part of our rapidly growing, forward-thinking engineering teams.

Architect comprehensive generative AI solutions centered on LLMs, Agentic, and RAG workflows. Collaborate with customers to understand and address language-based business challenges with tailored solutions. Partner with sales and business development for pre-sales support, including technical presentations and demonstrations. Provide feedback to NVIDIA engineering teams to contribute to generative AI technology advancements. Lead workshops and design sessions for defining and refining LLM and RAG solutions. Train and optimize Large Language Models using NVIDIA's hardware and software platforms. Implement effective strategies for LLM training and RAG workflow integration. Stay current with the latest developments in language models and generative AI technologies. Offer technical leadership and guidance on best practices for LLMs and RAG solutions. Work closely with Government, Research, and Public Sector departments.

Possess a B.Tech, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience. Demonstrate 10+ years of hands-on technical experience in generative AI, with a strong focus on LLM training. Showcase a proven record of deploying and optimizing LLM models for production inference. Exhibit in-depth knowledge of state-of-the-art language models (e.g., GPT-3, BERT). Expertise in training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Proficiency in model deployment and optimization for efficient inference on various hardware, especially GPUs. Strong understanding of GPU cluster architecture and parallel processing for accelerated training. Possess excellent communication and collaboration skills, with the ability to explain complex technical concepts. Experience leading workshops, training sessions, and technical presentations is essential.