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
