Engagement Tech Lead, Agentic AI

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $224,000–$356,500 / yr
Posted: 39 days ago
Freshness: Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $214k

This role $290k

$150k most similar roles pay here $379k

This role pays more than 88% of similar roles. Most pay $172,625–$254,437 — the shaded band above. At the midpoint, this role pays about $290k versus about $214k for comparable roles.

Based on 238 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Engagement Tech Lead, Agentic AI

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As the Engagement Tech Lead, Agentic AI, you will join a team focused on integrating Generative and Agentic AI software with high-priority Enterprise ISV partners. You will serve as a trusted advisor to Software Platform Architects, leading technical engagements to design and ship production agentic systems for demanding workloads. Your daily responsibilities include developing reference architectures for RAG, inference, and multi-agent workflows while providing feedback to internal Product, Engineering, and Research teams to shape the roadmap. You will work with technologies including NeMo, Nemotron, NeMo Agent Toolkit, NIM, Dynamo, TensorRT-LLM, vLLM, LangChain, vector DBs, MCP, and A2A. Required skills include Python, PyTorch, MLOps/LLMOps, Kubernetes, and Docker. You will solve complex problems in the agentic AI lifecycle, including fine-tuning, post-training, RL from verifiable rewards, reasoning, and production inference.

Skills

Agentic AI RAG Python PyTorch TensorRT-LLM vLLM LangChain NeMo Nemotron MLOps LLMOps Kubernetes Docker PEFT SFT

What you'll do

Lead technical engagements with high-priority ISV partners to define objectives and adoption plans for Generative and Agentic AI.
Design and ship production code, reference architectures, and workflows using NVIDIA’s software stack and open-source tools.
Implement advanced RAG, multi-agent systems, fine-tuning, and inference optimizations for enterprise-grade workloads.
Act as a trusted advisor to partner Software Platform Architects to drive the adoption of NVIDIA technologies.
Translate customer needs into actionable feedback for internal Product, Engineering, and Research teams to shape product roadmaps.
Manage the technical strategy and execution cadence for key accounts to ensure successful production deployments.
Provide expert guidance on agentic AI lifecycle components including evaluation, observability, and MLOps.

What we're looking for

12+ years of experience in technical Product, Engineering, or Solutions roles across enterprise software and production AI.
Master's degree or PhD in Computer Science, Electrical Engineering, or equivalent experience.
Strong AI/ML and deep learning foundation with hands-on experience building enterprise-grade GenAI systems.
Proficiency in Python and PyTorch.
Experience with the modern agent/LLM stack including LangChain, vLLM or TensorRT-LLM, vector DBs, and MCP/A2A.
Expertise in advanced RAG, multi-agent architectures, and production LLM deployments.
Solid grasp of enterprise deployment requirements including MLOps/LLMOps, Kubernetes, Docker, security, compliance, and governance.
Proven ability to lead technical engagements and build trust with senior engineers, architects, and executives.

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