Engagement Tech Lead, Agentic AI

🕒 July 14

🏄 California – Remote

🏄 California – Remote

💵 $224k - $431.3k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 5%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Lead the technical engagement with a focused set of ISV partners, working closely with their Software Platform Architects. • Together you'll set the objectives, timelines, and adoption plan for each account. • 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. Bring their needs and architecture to our Product, Engineering, and Research teams, and help shape the roadmap with what you see across industries. • 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). • Direct experience with every tool is not required. • Solid grasp of enterprise deployment: MLOps/LLMOps, Kubernetes and Docker, and security, compliance, and governance. • The range to research, prototype, and collaborate across teams, and execution rigor to carry the best solution through to production.

🏖️ Benefits

• equity • benefits