Senior Solutions Architect, Agentic AI - Public Sector

We Love AI Jobs; Gurugram District; On-site; INR 4,000,000 - 8,500,000; Full time

Job summary

NVIDIA in India, Gurugram, is seeking a Senior Solutions Architect to design generative AI solutions for public sector clients. The role focuses on training, deployment, and RAG workflows using LLMs on NVIDIA platforms.

The candidate leads workshops, collaborates with pre-sales and customers, and guides engineering teams to deliver production-ready AI solutions with scale and reliability.

Qualifications

• 10+ years in a technical role with generative AI focus.
• Proven track record deploying LLMs for production inference.
• Experience with GPT-3, BERT or similar architectures.

Responsibilities

• Architect end-to-end generative AI solutions with LLMs, agentic workflows and RAG.
• Lead workshops, pre-sales activities and customer demonstrations.
• Train, fine-tune, and optimize LLMs for NVIDIA platforms.

Skills

LLMs

RAG workflows

Agentic AI

PyTorch

TensorFlow

Hugging Face

GPU clusters

Education

B.Tech / MS / PhD in CS or AI

Tools

TensorFlow

PyTorch

Hugging Face Transformers

Job description

# Senior Solutions Architect, Agentic AI - Public SectorNVIDIAIndia, GurugramFull-timeAI tools:GPT-3BERTTensorFlowPyTorchHugging FaceUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageDesigns and delivers generative AI solutions for public-sector customers, with an emphasis on LLM training, inference, and retrieval-augmented generation. The role combines hands-on model work with customer workshops, technical guidance, and pre-sales collaboration.* Permanent* On-site* 10+ years* Bachelor's, Master's, or PhD### Skills and expertiseLarge language modelsRAG workflowsAgentic AILLM training and fine-tuningPyTorchTensorFlowHugging Face TransformersGPU cluster architecture### Key responsibilities* Architect generative AI solutions centered on LLMs, agentic workflows, and RAG.* Train, optimize, and deploy LLMs for production inference on NVIDIA platforms.* Lead customer workshops and support technical presentations and demonstrations.## How this job comparesCompared with 410 open senior machine learning jobs on October 10, 2026.Similar open jobs: We Love AI Jobs lists 410 open senior machine learning jobs at 176 companies.Remote work: This job is on site. 90 of the 410 senior machine learning jobs (22%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. The role centers on training, fine-tuning, optimizing, and deploying LLMs, as well as designing agentic and RAG workflows. These are hands-on AI responsibilities.## Full descriptionNVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with specialized expertise in training Large Language Models (LLMs) and Agentic AI . As a key member of our AI Solutions team, you will play a pivotal role in architecting and delivering cutting-edge solutions that leverage the power of NVIDIA's generative AI technologies. This position requires a deep understanding of language models, particularly LLMs, and a strong proficiency in designing and implementing agentic and RAG-based workflows.What you will be doing:• 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 departmentsWhat we need to see:• 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.Ways to stand out from the crowd:• 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 clustersWith competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you!