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Senior Solutions Architect, Generative AI

NVIDIA· Architect, Solutions
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MumbaiFull-timePosted 1mo ago

About the role

Senior Solutions Architect focused on Generative AI with expertise in training Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG); responsible for end-to-end solution design, customer engagement, pre-sales support, and collaboration with NVIDIA engineering to advance generative AI technologies.

Responsibilities

  • Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows.
  • Collaborate closely with customers to understand 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.

Qualifications

  • Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience
  • 5+ 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 TensorFlow, PyTorch, or Hugging Face Transformers
  • Proficiency in model deployment and optimization techniques for efficient inference on GPUs
  • Strong knowledge of GPU cluster architecture and parallel processing for accelerated training and inference
  • Excellent communication and collaboration skills
  • Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences

Skills

Required:LLM training and fine-tuningRAG workflow designGPU-based model deployment

Benefits

  • Competitive salaries
  • Generous benefits package
  • Diversity and equal opportunity employer
  • On-site work in Mumbai, India
Last updated Sep 18, 2026. Interested? Apply on the company site.

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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