GenAI Engagement Architect

NVIDIA; United States; On-site; USD 224,000 - 431,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a highly technical Engagement Lead to drive integration of Generative and Agentic AI with our Enterprise ISV partners. You will lead the technical engagement, design production agentic systems, and accelerate adoption of NVIDIA's stack across priority initiatives.

This role requires a strong AI/ML foundation, hands-on execution, and the ability to work with Product, Engineering, and Research to shape roadmaps and deliver scalable solutions for senior leaders.

Qualifications

• 12+ years in technical Product, Engineering, or Solutions roles across enterprise software and production AI.
• 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.
• Proficiency in Python and PyTorch and the modern agent/LLM stack.

Responsibilities

• Lead the technical engagement with ISV partners, setting objectives, timelines, and adoption plans.
• Design and ship code, methods, and reference architectures for RAG, inference, and multi-agent workflows.
• Drive the technical strategy, cadence, and adoption analytics with Product, Engineering, Research teams.
• Build breadth across the AI lifecycle with depth in PEFT, post-training, RL, reasoning, and production inference.
• Represent partner needs inside NVIDIA and influence roadmap with cross-functional teams.

Skills

Python

PyTorch

LangChain

vLLM

TensorRT-LLM

Vector DBs

Kubernetes

Docker

RAG

Multi-agent

Education

Masters or PhD in CS/EE

Tools

NeMo

Nemotron

NeMo Agent Toolkit

NIM

Dynamo

TensorRT-LLM

vLLM

LangChain

Vector DBs

MCP

A2A

Job description

NVIDIA is seeking a highly technical Engagement Lead to drive integration of Generative and Agentic AI with our Enterprise ISV partners. You will lead the technical engagement, design production agentic systems, and accelerate adoption of NVIDIA's stack across priority initiatives.

This role requires a strong AI/ML foundation, hands-on execution, and the ability to work with Product, Engineering, and Research to shape roadmaps and deliver scalable solutions for senior leaders.