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Senior Solution Architect, Generative AI - CSP

NVIDIA· Architect, Solutions
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Bengaluru, India, Mumbai, Indiaon-sitePosted 2mo ago

About the role

AI-focused Solution Architect focusing on Large Language Models (LLMs), generative AI, and RAG workflows, responsible for architecting end-to-end generative AI solutions, collaborating with customers and NVIDIA engineering, and leading workshops and training on LLMs with NVIDIA hardware/software.

Responsibilities

  • Architect end-to-end generative AI solutions with a focus on LLMs training, deployment and RAG workflows.
  • Collaborate closely with customers to understand their language-related business challenges and design tailored solutions.
  • Work closely with NVIDIA engineering teams to provide feedback and contribute to the evolution of generative AI software.
  • Engage directly with customers/partners to understand their 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.
  • Provide technical leadership and guidance on best practices for training LLMs and implementing RAG-based solutions.

Qualifications

  • Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience
  • 7+ years of hands-on experience in a technical AI 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.
  • Expertise in training and fine-tuning LLMs using popular frameworks such as Megatron-LM, Megatron-Bridge, AutoModel and PyTorch.
  • 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.

Skills

Required:Generative AI and LLMsModel training and fine-tuningDeployment and optimization for inferenceGPU cluster architectureCommunication and stakeholder management
Last updated Aug 21, 2026. Interested? Apply on the company site.

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