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# Solutions Architect, Agentic AI

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Computer Programming, Software Debugging, Distributed Systems, Python (Programming Language), Linux System Administration, Machine Learning, OpenAI, Tensorflow, AI Infrastructure, Enterprise Software Applications, Pytorch, LangChain, Retrieval-Augmented Generation, Transfer Learning, Large Language Models, Multi-Agent Systems, Deep Learning, Model Validation, NeMo Guardrails, Llamaindex, Generative AI, Agentic-AI, Information Technology, CrewAI, TensorRT, Nim (Programming Language), Semantic Kernel
- **Published:** October 11, 2026
- **Apply:** https://www.juju.com/job/1_ScrapingHub33470-JR2021199

## About the Role

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, policy enforcement, OpenShell-like environments, or secure enterprise agent runtime build. + Recognized expertise in RAG, model customization, agent orchestration, enterprise AI security, or GPU-accelerated AI infrastructure, with field-facing technical presence through workshops, architecture reviews, talks, whitepapers, or developer enablement.