Lead Enterprise Agentic AI Architect

NVIDIA Corporation; Santa Clara (CA); Remote; USD 184,000 - 288,000; Full time

Job summary

NVIDIA Corporation is seeking a Senior Solutions Architect for its Agentic AI program in Santa Clara. You will lead technical delivery for strategic partner engagements, architect enterprise-grade agentic systems, and drive production deployment from PoC to scale across OpenShell, OpenAI Agents SDK, and other frameworks.

You will guide partners on model customization, post-training workflows, and performance optimization, shaping enterprise AI strategies with NVIDIA’s GPU-accelerated platform.

Qualifications

• 8+ years of engineering, solutions architecture, or deployment experience.
• Proven track record leading complex AI or enterprise deployments.
• Hands-on experience with LLM, generative AI, or RAG in production.
• Strong Python and Linux skills; PyTorch or TensorFlow experience.
• Understanding of agentic AI architectures, guardrails, and failure handling.

Responsibilities

• Lead technical delivery for Agentic AI partner engagements from discovery to scale.
• Design enterprise-grade agentic systems, including multi-agent workflows and RAG-enabled apps.
• Lead architecture reviews balancing model quality, latency, cost, safety and observability.
• Build PoCs, benchmarks, reference architectures, and reusable blueprints for production deployments.
• Guide partners on model customization and post-training workflows (SFT, RL).

Skills

Engineering experience

Solutions architecture

Applied ML

Python

Linux

PyTorch

TensorFlow

Communication

Education

BS/MS/PhD in CS/EE/AI

Tools

OpenShell

OpenAI Agents SDK

LangGraph

LlamaIndex

LangChain

Job description

NVIDIA Corporation is seeking a Senior Solutions Architect for its Agentic AI program in Santa Clara. You will lead technical delivery for strategic partner engagements, architect enterprise-grade agentic systems, and drive production deployment from PoC to scale across OpenShell, OpenAI Agents SDK, and other frameworks.

You will guide partners on model customization, post-training workflows, and performance optimization, shaping enterprise AI strategies with NVIDIA’s GPU-accelerated platform.