# Solutions Architect, Agentic AI

**Company**: NVIDIA
**Location**: Santa Clara
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Salary**: Competitive salary and benefits package
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Solutions-Architect--Agentic-AI_JR2014517?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_7307dfde-bb1

## 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.

As a trusted advisor, you'll transform raw LLM capabilities into high-performance, industry-focused enterprise agents.

**Key Responsibilities:**

- 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.

**Requirements:**

- 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 LangGraph, LlamaIndex, CrewAI, LangChain, or OpenAI Agents SDK.

- 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.

**Nice to Have:**

- 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.

## Skills

### Required
- Python
- C/C++
- Linux
- PyTorch
- TensorFlow
- LangGraph
- LlamaIndex
- CrewAI
- LangChain
- OpenAI Agents SDK

### Nice to have
- NVIDIA NIM
- NeMo Framework
- NeMo Retriever
- NeMo Agent Toolkit
- LLM evaluation frameworks
- benchmarking systems
- safety guardrails
- Kubernetes/OpenShift
- CI/CD automation
- cloud-native deployment patterns

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Solutions-Architect--Agentic-AI_JR2014517?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)