Engagement Tech Lead, Agentic AI

What you'll do

• Set partner objectives, timelines, and adoption plans; lead technical strategy and execution.
• Design and ship code, methods, and reference architectures for RAG, inference, and multi-agent workflows.
• Represent partner needs to NVIDIA Product, Engineering, and Research teams and share deployment insights to inform solutions and roadmaps.

What they ask for

• 12+ years in technical Product, Engineering, or Solutions roles across enterprise software and production AI, including customer- or partner-facing work.
• Master’s or PhD in Computer Science or Electrical Engineering, or equivalent experience.
• Hands-on experience building enterprise-grade GenAI systems, including advanced RAG, multi-agent architectures, and production LLM deployments.
• Proficiency in Python and PyTorch; knowledge of modern agent/LLM tools and enterprise deployment, including MLOps/LLMOps, Kubernetes, Docker, security, compliance, and governance.

Nice to have

• Track record of influencing product decisions through partner relationships and translating customer needs into scalable platform improvements.
• In-depth knowledge of the ISV and cloud provider landscape; experience delivering outcomes in high-stakes partner collaborations.

Pay

224,000 USD - 356,500 USD (base salary, Level 5); 272,000 USD - 431,250 USD (base salary, Level 6)

Tools

Python, PyTorch, LangChain, vLLM, TensorRT-LLM, Kubernetes, Docker, NeMo

AI focus

Build and deploy production agentic AI, including RAG, inference, multi-agent workflows, fine-tuning, post-training and RL, reasoning, agent evaluation and observability, and production inference.