Solutions Architect, Agentic AI

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.
• What we need to see:
• 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
• 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.
• Ways to Stand Out from the Crowd:
• 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.
• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits .
• Applications for this job will be accepted at least until May 17, 2026. This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.

Additional Information

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.

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