Solutions Architect, Agentic AI

Nvidia

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $152,000–$241,500 / yr
Posted: 24 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $207k

This role $197k

$139k most similar roles pay here $270k

This role pays less than 63% of similar roles. Most pay $167,652–$246,150 — the shaded band above. At the midpoint, this role pays about $197k versus about $207k for comparable roles.

Based on 240 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 563 open roles on FindRole.

Listed pay typically runs $168,000–$264,500 across 556 roles with salary data.

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At a glance

TL;DR · Solutions Architect, Agentic AI

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As a Solutions Architect at NVIDIA, you will join the cutting-edge Agentic AI team to guide enterprise software companies in building sophisticated AI-native systems. Your daily tasks include developing complex agentic systems with multi-agent coordination and advanced planning frameworks, optimizing inference performance using GPU-accelerated technologies like PyTorch or TensorFlow, and creating production-grade deployment blueprints through hands-on PoCs and reference architectures. You will work closely with internal teams to enhance NVIDIA’s AI infrastructure stack and empower partner engineering teams via technical workshops and deep-dive reviews. Ideal candidates have over five years of experience in deep learning and distributed AI systems, strong programming skills in Python and C/C++, and hands-on experience with agentic frameworks like LangGraph or LlamaIndex, as well as familiarity with NVIDIA’s core technologies such as NIM and NeMo Framework.

Skills

Python PyTorch TensorFlow NVIDIA NIM NeMo Framework Dynamo Nemo Agent Toolkit LangGraph LlamaIndex CrewAI LangChain OpenAI Agents SDK Kubernetes CI/CD PostgreSQL Linux CUDA Prometheus Grafana

What you'll do

Build complex agentic systems featuring multi-agent coordination and advanced planning frameworks.
Develop full-scale solutions including high-performance retrieval pipelines spanning various data sources.
Optimize inference performance using GPU-accelerated frameworks and NVIDIA’s AI infrastructure stack.
Create hands-on PoCs and reference architectures for production-grade generative AI pipelines.
Empower partner engineering teams through technical workshops and deep-dive architecture reviews.
Craft reusable assets and documentation to deploy agentic AI at scale globally.

What we're looking for

Over 5 years of experience in deep learning, machine learning, or distributed AI systems.
Strong programming skills in Python, C/C++, and Linux environments.
Hands-on experience building LLM and generative AI applications.
Experience with agentic or multi-agent AI frameworks like LangGraph, LlamaIndex, and LangChain.
Ability to prototype AI applications and build scalable GPU-accelerated architectures.
Expertise in NVIDIA GPUs and AI software including NIM, NeMo Framework, and NeMo Agent Toolkit.
Familiarity with Kubernetes/OpenShift, CI/CD automation, and cloud-native deployment patterns for AI systems.

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