Senior Solutions Architect, Generative AI
NVIDIA Corporation (company site, opens in a new tab)10+ yrsGurugramOn-siteDirect career pageEst. 50–95 LPA
Posted on 8 Sept
Reach people at NVIDIA Corporation
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at NVIDIA Corporation you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Architect and deliver end-to-end generative AI solutions focused on Large Language Models (LLMs), Agentic, and Retrieval-Augmented Generation (RAG) workflows.
- Lead training, optimization, and integration of LLMs using NVIDIA’s hardware and software platforms for customer applications.
- Collaborate with customers, sales, and engineering teams to tailor solutions, support pre-sales, and contribute to generative AI technology evolution.
Minimum Requirements
- 10+ years of hands-on experience in generative AI with strong emphasis on training Large Language Models (LLMs).
- Degree requirement: B.Tech, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
- Proven experience deploying and optimizing LLMs for production inference environments, using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.
- Strong knowledge of GPU cluster architecture and proficiency in leveraging GPUs for LLM training and inference.
Ideal Candidate Profile
- Experienced in architecting scalable AI solutions involving LLMs, agentic AI, and RAG workflows in complex environments.
- Technically proficient in model deployment optimizations including containerization (Docker) and orchestration (Kubernetes) for GPU clusters.
- Capable of leading technical workshops and collaborating across customer, sales, and engineering teams with clear communication.