Senior Solutions Architect, Agentic AI - Public Sector
NVIDIA · Posted Sep 27
Graphics processing units, artificial intelligence platforms, accelerated computing, and data center solutions
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About the role
NVIDIA's AI Solutions team architect and deliver generative AI solutions built on NVIDIA's hardware and software platforms. The role centers on Large Language Models, Agentic AI, and RAG-based workflows for Government, Research, and Public Sector customers. This Senior Solutions Architect will design end-to-end generative AI solutions, lead workshops and design sessions, support pre-sales technical activities, and guide customers on training, deploying, and optimizing LLMs.
What you will do
- Architect end-to-end generative AI solutions with a focus on LLMs, Agentic and RAG workflows.
- Collaborate closely with customers to understand their language-related business challenges and design tailored solutions.
- Collaborate with sales and business development teams to support pre-sales activities, including technical presentations and demonstrations of LLM and RAG capabilities.
- Work closely with NVIDIA engineering teams to provide feedback and contribute to the evolution of generative AI technologies.
- Engage directly with customers to understand their language-related requirements and challenges.
- Lead workshops and design sessions to define and refine generative AI solutions focused on LLMs and RAG workflows and lead the training and optimization of Large Language Models using NVIDIA’s hardware and software platforms.
- Implement strategies for efficient and effective training of LLMs to achieve optimal performance.
- Design and implement RAG-based workflows to enhance content generation and information retrieval.
- Work closely with customers to integrate RAG workflows into their applications and systems and stay abreast of the latest developments in language models and generative AI technologies.
- Provide technical leadership and guidance on best practices for training LLMs and implementing RAG-based solutions.
- Collaborating and working with Government, Research and Public sector departments
Skills used in this role
What the employer is looking for
- B.Tech ,Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience
- 10+ years of hands-on experience in a technical role, specifically focusing on generative AI, with a strong emphasis on training Large Language Models (LLMs).
- Proven track record of successfully deploying and optimizing LLM models for inference in production environments.
- In-depth understanding of state-of-the-art language models, including but not limited to GPT-3, BERT, or similar architectures.
- Expertise in training and fine-tuning LLMs using popular frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
- Proficiency in model deployment and optimization techniques for efficient inference on various hardware platforms, with a focus on GPUs.
- Strong knowledge of GPU cluster architecture and the ability to leverage parallel processing for accelerated model training and inference.
- Excellent communication and collaboration skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
- Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences.
Preferred qualifications
- Proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization.
- Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment.
- Deep understanding of GPU cluster architecture, parallel computing, and distributed computing concepts.
- Hands-on experience with NVIDIA GPU technologies, and GPU cluster management and ability to design and implement scalable and efficient workflows for LLM training and inference on GPU clusters
Benefits and support
- Compensation and benefits are detailed in the job posting
About NVIDIA
NVIDIA Corporation is a multinational technology company that designs graphics processing units (GPUs) for the gaming and professional markets, as well as system on a chip units (SoCs) for the mobile computing and automotive market. Pioneering accelerated computing, the company has become a driving engine of modern artificial intelligence, deep learning, and data center infrastructure.
- Industry
- Semiconductors
- Company size
- 42000+ employees
- Founded
- April 5, 1993
- Location
- Santa Clara, California, USA
- Funding stage
- Public Company
Funding
Public Company · $5M raised
Leadership
Founder, President and Chief Executive Officer
Executive Vice President and Chief Financial Officer
Founder and NVIDIA Fellow
Executive Vice President, Worldwide Field Operations
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