Senior Solutions Architect, Agentic AI
NVIDIA· Architect, Solutions
Hybrid (Remote / Santa Clara, CA)$184k - $287.5kfull-timePosted 3mo ago
About the role
Senior Solutions Architect to design, build, optimize, and deploy production-grade Agentic AI systems on NVIDIA’s accelerated computing platform for Enterprise ISVs, spanning multi-agent orchestration, RAG, tool use, model customization, and production deployment.
Responsibilities
- 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.
Qualifications
- 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.
Skills
Required:PythonLinuxPyTorchAgentic AI architectures
Nice to have:TensorFlow
Benefits
- equity
- comprehensive benefits package (NVIDIA benefits)
Last updated Jul 17, 2026. Interested? Apply on the company site.
About NVIDIA
World Leader in AI Computing
NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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