Senior Solutions Architect, Agentic AI

We are looking for a Senior Solutions Architect to help leading Enterprise ISVs design, build, optimize, and deploy production-grade Agentic AI systems on NVIDIA’s accelerated computing platform. In this role, you will partner with strategic software companies to translate frontier AI capabilities into reliable enterprise products, spanning multi-agent orchestration, RAG, tool use, model customization, and production deployment.   We work at the intersection of partner engineering, NVIDIA’s AI platform, and product development. You will lead sophisticated technical projects from initial exploration through architecture, prototyping, performance optimization, production rollout, and field enablement. Together, we will help partners adopt NVIDIA technologies and GPU-accelerated infrastructure to bring next-generation AI products to market.   What you'll be doing: • Lead technical delivery for strategic Agentic AI partner engagements from discovery and architecture through PoC, production readiness, rollout, and scale. • Design and build enterprise-grade agentic systems, including multi-agent workflows, tool-using agents, RAG-integrated applications, planning, memory, evaluation, and guardrail patterns. • Lead deep architecture reviews with partner engineering teams, driving tradeoffs across model quality, latency, efficiency, cost, retrieval quality, reliability, safety, security, and observability. • Build hands-on PoCs, benchmarks, reference architectures, and reusable blueprints that help Enterprise ISVs and NVIDIA field teams move from exploration to production. • Guide partners on model customization and post-training workflows, including supervised fine-tuning, reinforcement learning methods, human or AI feedback, direct preference optimization, PEFT/LoRA, synthetic data generation, evaluation, and regression analysis. • Work with agent harnesses and execution environments such as OpenShell, OpenAI Agents SDK, LangGraph, LlamaIndex, LangChain, CrewAI, Semantic Kernel, or similar frameworks. • Translate partner deployment findings into actionable feedback for NVIDIA Product and Engineering, so we can improve our platforms, tools, and field guidance. What we need to see: • 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 or relevant equivalent experience, reward modeling, LoRA/PEFT, quantization-aware optimization, or model evaluation. • Ability to lead ambiguous partner engagements, influence senior engineering collaborators, and communicate clearly with technical and executive audiences. Ways to stand out from the crowd: • Hands-on experience with NVIDIA AI software such as NIM, NeMo Framework, NeMo Retriever, NeMo Guardrails, NeMo Agent Toolkit, Dynamo, Nemotron, Triton, TensorRT-LLM, or NIM Operator. • Experience building post-training pipelines for reasoning, tool use, domain adaptation, enterprise task performance, or agent behavior improvement. • Experience with agent harnesses, sandboxed execution, pol