Solutions Architect, Gen AI, NVIDIA

Generative AI, Solution Architect
India, Bengaluru
February 26, 2026
Full Time

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Job Description

NVIDIA is searching for a Solutions Architect who specializes in Generative AI to create and implement complete AI systems which use Large Language Models and Agentic AI and RAG-based workflows. The position requires the person to work together with customers and sales staff and NVIDIA engineers to create and implement advanced generative AI systems which function on NVIDIA GPU platforms.

Date Posted: NA

Expiration Date: NA

Qualification: B.Tech / Master’s / Ph.D. in Computer Science, Artificial Intelligence, or equivalent

Experience: 8+ Years

Job ID: JR2010605

Role: Solutions Architect, Generative AI

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Primary Responsibilities

  • Develop complete generative AI systems which depend on LLMs and Agentic AI and RAG workflows.
  • Work with customers to analyze their business problems and create customized AI solutions.
  • Provide technical presentations to support pre-sales activities while demonstrating product capabilities.
  • Work with NVIDIA engineers to shape future developments of generative AI technologies.
  • Conduct workshops and design sessions which focus on developing LLM and RAG-based solutions.
  • Use NVIDIA hardware and software platforms to train and fine-tune and optimize Large Language Models.
  • Create RAG workflows to improve content generation and information retrieval processes.
  • Offer technical expertise about effective LLM training methods and deployment strategies and optimization techniques for inference operations.

Basic Requirements

  • At least 8 years of practical experience working with generative AI technology which includes special expertise in training LLMs.
  • Demonstrate successful experience with LLM deployment and optimization for real-time production use.
  • Operate at an expert level with current language models which include GPT and BERT and other comparable systems.
  • Advanced skills in using TensorFlow and PyTorch and Hugging Face Transformers.
  • Deep expertise about GPU system designs together with their operational capacities and method for training across multiple devices.
  • Demonstrates exceptional communication abilities which enable them to make complicated ideas understandable to others.

Preferred Qualifications

  • Developed expertise in boosting LLM systems through enhancement of their processing speed and storage usage and operational efficiency.
  • knowledge of Docker and Kubernetes which enables them to create AI systems that can expand according to demand. 
  • Hands-on experience with NVIDIA GPU technologies and GPU cluster management.

Complete understanding of how to create and implement generative AI systems at an enterprise level which can operate across multiple business locations.

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