Senior Solutions Architect, Agentic AI

What you'll do

• Lead technical delivery for strategic Agentic AI partner engagements from initial discovery through production rollout and scale.
• Design and build enterprise-grade agentic systems featuring multi-agent workflows, RAG integration, tool use, and guardrail patterns.
• Conduct deep architecture reviews to balance tradeoffs between model quality, latency, cost, reliability, and security.
• Build hands-on PoCs, benchmarks, and reusable blueprints to move partners from AI exploration to production.
• Guide partners on model customization workflows including supervised fine-tuning, reinforcement learning, and synthetic data generation.
• Implement agent harnesses and execution environments using frameworks like LangGraph, LlamaIndex, or CrewAI.
• Translate partner deployment findings into actionable feedback for NVIDIA Product and Engineering teams to improve platforms.

What we're looking for

• BS/MS/PhD in Computer Science, Electrical Engineering, AI/ML, or equivalent experience.
• 8+ years of engineering, solutions architecture, applied ML, or technical deployment experience.
• Consistent track record leading complex AI, ML, distributed systems, or enterprise software deployments from prototype to production.
• Hands-on experience building LLM, generative AI, RAG, or agentic AI applications in production or production-like environments.
• Strong programming and debugging skills in Python and Linux environments with experience in PyTorch, TensorFlow, or similar deep learning frameworks.
• Deep understanding of agentic AI architectures, including tool use, orchestration, memory, retrieval, planning, evaluation, guardrails, and failure handling.
• Experience with model customization or post-training techniques such as SFT, RL/RLHF/RLAIF, DPO, LoRA/PEFT, or quantization-aware optimization.
• Hands-on experience with NVIDIA AI software such as NIM, NeMo Framework, Triton, or TensorRT-LLM (preferred).