NVIDIA Solution Architect

Job Description Must Have Technical/Functional Skills 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 Roles & Responsibilities Solution Architecture & Delivery 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 Salary Range: $180,000 to $200,000 per year Qualifications: BACHELOR OF COMPUTER SCIENCE Show more Show less