Engagement Tech Lead, Agentic AI

NVIDIA is seeking a highly technical Engagement Lead to drive integration of Generative and Agentic AI software with its highest-priority Enterprise ISV partners.

In this role, you will lead the technical engagement with a select set of the world's most strategic enterprises as the trusted advisor their Software Platform Architects trust, and the leader who unites everyone working the account behind one technical vision.

You'll stay hands-on, designing and shipping the production agentic systems that run their most demanding workloads, while accelerating adoption of NVIDIA's stack across the initiatives that shape their business.

Responsibilities:

• Lead the technical engagement with a focused set of ISV partners, working closely with their Software Platform Architects.
• Stay hands-on: design and ship the code, methods, and reference architectures that bring RAG, inference, and multi-agent, long-horizon workflows to life on our stack (NeMo, Nemotron, NeMo Agent Toolkit, NIM, Dynamo, TensorRT-LLM) and open tools (vLLM, LangChain, vector DBs, MCP, A2A).
• Lead the technical strategy and execution: run the cadence, track adoption, and share what you learn with our Product, Engineering, Research, and Solution Architecture teams to land the best solution.
• Build breadth across the agentic AI lifecycle, with depth in a few areas that fit you: fine-tuning (PEFT, SFT), post-training and RL from verifiable rewards, reasoning, advanced RAG, multi-agent workflows, skills/harness engineering, agent evaluation and observability, and production inference.
• Be the voice of the partner inside NVIDIA.
• Grow deep expertise in agentic platform architecture, and keep up with our fast-moving field and stack so you can give partners the best guidance.

Requirements:

• 12+ years in technical Product, Engineering, or Solutions roles across enterprise software and production AI, including customer- or partner-facing work.
• Masters or PhD in Computer Science, Electrical Engineering, or equivalent experience.
• A strong AI/ML and deep learning foundation, with hands-on experience building enterprise-grade GenAI systems: advanced RAG, multi-agent architectures, and production LLM deployments.
• You enjoy leading technical engagements with customers, earning the trust of senior engineers, architects, and executives, and bringing a cross-functional team along.
• Proficiency in Python and PyTorch and the modern agent/LLM stack (LangChain, an inference engine like vLLM or TensorRT-LLM, vector DBs, MCP/A2A).
• Solid grasp of enterprise deployment: MLOps/LLMOps, Kubernetes and Docker, and security, compliance, and governance.

Benefits:

• Equity
• Benefits