NVIDIA Solution Architect - AI / GenAI & Agentic AI

Ventures Unlimited
Edison, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Edison, United States of America

Tech stack

Artificial Intelligence
Computer Clusters
Profiling
Nvidia CUDA
Data Cleansing
Distributed Computing Environment
Ethernet
InfiniBand
TensorFlow
AI Infrastructure
Graphics Processing Unit (GPU)
PyTorch
Large Language Models
Multi-Agent Systems
Model Validation
TensorRT
Virtual Agents
Nim (Programming Language)

Job description

  • Design end-to-end AI / GenAI and agentic architectures using NVIDIA GPUs, DGX/HGX platforms, networking, and NVIDIA AI stack (NeMo, NIM, Triton, TensorRT?LLM, RAPIDS)
  • Build PoCs and reference architectures for LLMs, RAG, agentic AI, and industry-specific use cases
  • Optimize training and inference performance across distributed GPU clusters

AI Agent Lifecycle (NeMo?Powered)

  • Enable the full AI agent lifecycle: data preparation, model selection, agent orchestration, deployment, and continuous optimization
  • Use NeMo Curator & Data Designer for AI?ready and synthetic data
  • Apply Nemotron models, NeMo Retriever, and NeMo Evaluator for RAG and validation
  • Build and optimize agents using NeMo Agent Toolkit across LangChain, CrewAI, LangGraph, and custom frameworks
  • Deploy high?performance inference using NVIDIA NIM
  • Enforce grounding, safety, and compliance using NeMo Retriever and NeMo Guardrails
  • Drive continuous improvement using NeMo Customizer, NeMo RL, and NeMo Evaluator

Customer & Partner Engagement

  • Act as a trusted technical advisor to enterprise customers, GSIs, ISVs, and cloud partners
  • Lead architecture workshops and deep?dive sessions with CXOs, architects, and engineering teams
  • Translate business problems into scalable NVIDIA?based solutions with measurable outcomes

Ecosystem & Enablement

  • Enable partners on NVIDIA AI Enterprise and cloud reference architectures
  • Create reusable assets: demos, reference architectures, and enablement material
  • Provide field feedback to influence NVIDIA product roadmap

Requirements

AI / GenAI

  • Hands?on experience with LLMs, RAG, agentic workflows, and GenAI architectures
  • Frameworks: PyTorch, TensorFlow
  • NVIDIA stack: NeMo, NIM, Triton, TensorRT?LLM, RAPIDS
  • Custom LLM development experience (LoRA, QLoRA, distillation, hyperparameter tuning)
  • Experience using NVIDIA Nemotron models

GPU & Systems

  • GPU acceleration, CUDA fundamentals, performance profiling
  • Distributed training and inference on multi?node GPU clusters
  • AI networking and storage concepts (InfiniBand / Ethernet)

Nice to Have

  • Experience with LangGraph, LlamaIndex, CrewAI
  • Industry expertise (BFSI, Healthcare, Retail, Manufacturing)
  • NVIDIA Certifications (AI Infrastructure, GenAI, AI Operations)
  • Enables scalable, governed adoption of GenAI and AI agents

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