Senior Solutions Architect, Retail

Join NVIDIA as a Solutions Architect to own the evolution of Agentic AI for the enterprise. You will collaborate with top-tier Retail 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.

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.
• 8+ 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.

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.
• Background with LLM evaluation frameworks, benchmarking systems, and safety guardrails for agentic workflows.
• Experience with pre-training/fine-tuning techniques like SFT, LoRA, DPO, PPO, GRPO, DAPO, or RLVF
• Experience optimizing reasoning-focused LLMs through timely engineering, quantization, or benchmarking.
• Background with parallel or distributed computing environments and AI workloads optimized for GPUs.