Solutions Architect, Agentic AI at NVIDIA

You're a mid-level Solutions Architect with a strong background in deep learning, machine learning, or distributed AI systems, likely holding a BS/MS/PhD in a r

Work type: remote

Location: US, CA, Santa Clara | US, Remote

Salary: $152,000 – $241,500/yr

Type: Full-time

Summary

You're a mid-level Solutions Architect with a strong background in deep learning, machine learning, or distributed AI systems, likely holding a BS/MS/PhD in a related field or equivalent experience, and over 5 years of relevant professional work. **What makes it worth a look...** NVIDIA is hiring for this fully remote, full-time Solutions Architect, Agentic AI role, offering a base salary range of $152,000 - $241,500 USD, plus equity. **You might be a good fit if you...** * Have 5+ years of experience in deep learning, machine learning, or distributed AI systems. * Possess strong programming and debugging skills in Python, C/C++, and Linux, with experience in deep learning libraries like PyTorch or TensorFlow. * Have hands-on experience building LLM and generative AI applications, specifically with agentic or multi-agent AI systems using frameworks like LangGraph, LlamaIndex, CrewAI, LangChain, or OpenAI Agents SDK. * Can rapidly prototype AI applications and build scalable GPU-accelerated architectures.

Job Description

Join NVIDIA as a Solutions Architect to own the evolution of Agentic AI for the enterprise. You will collaborate with top-tier enterprise software companies to build and deploy sophisticated AI-native systems, focusing on multi-agent coordination, RAG-integrated workflows, and accelerated inference. By mastering NVIDIA’s core technologies—NIM, NeMo Framework, Dynamo, and Nemo Agent Toolkit—you will guide partners through the complexities of performance optimization and production-grade deployment. As a trusted advisor, you’ll transform raw LLM capabilities into high-performance, industry-focused enterprise agents.

What you'll be doing:

• Build complex agentic systems featuring multi-agent coordination, long-horizon reasoning, and advanced planning frameworks.

• Develop full-scale solutions, including domain-specific enterprise agents and high-performance retrieval pipelines (RAG) spanning various data sources.

• Optimize inference performance by bringing to bear GPU-accelerated frameworks and the full NVIDIA AI infrastructure stack.

• Build hands-on PoCs and reference architectures that serve as the blueprint for production-grade generative AI pipelines.

• Collaborate alongside Enterprise ISVs to integrate NVIDIA software into native platforms, accelerating the deployment of production workloads.

• Collaborate with diverse internal teams to improve NVIDIA software through feedback from real-world implementations.

• Empower partner engineering teams through technical workshops, deep-dive architecture reviews, and developer enablement.

• Scale global expertise by crafting reusable assets and documentation that help field teams deploy agentic AI at scale.

• BS/MS/PhD in Computer Science, Electrical Engineering, AI/ML, or equivalent experience.

• More than 5 years of experience in deep learning, machine learning, or distributed AI systems.

• Strong programming and debugging experience in Python, C/C++, and Linux environments.

• Background in using deep learning libraries like PyTorch or TensorFlow.

• Hands-on experience building LLM and generative AI applications.

• Experience working with agentic or multi-agent AI systems employing frameworks such as:

2. LlamaIndex

3. CrewAI

4. LangChain

5. OpenAI Agents SDK or similar orchestration frameworks

• Experience building tool-using AI agents that interact with APIs, databases, and enterprise systems.

• Ability to rapidly prototype AI applications and build scalable GPU-accelerated architectures.

• Excellent interpersonal skills and the ability to collaborate with engineering teams, partners, and executive collaborators.

• Experience working with NVIDIA GPUs and AI software, such as NVIDIA NIM, NeMo Framework, NeMo Retriever, and NeMo Agent Toolkit.

• Experience with LLM evaluation frameworks, benchmarking systems, and safety guardrails for agentic workflows.

• Experience optimizing reasoning-focused LLMs through timely engineering, quantization, or benchmarking.

• Familiarity with Kubernetes/OpenShift, CI/CD automation, and cloud-native deployment patterns for AI systems.

• Experience with parallel or distributed computing environments and AI workloads optimized for GPUs.

You will also be eligible for equity and [benefits](https://www.nvidia.com/en-us/benefits/).

Applications for this job will be accepted at least until April 19, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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