AMDAI Solutions Architect

THE ORGANIZATION: The Physical AI and Vertical Software & Solutions (PAVS) organization is dedicated to accelerating the adoption of Physical AI across robotics, industrial, and automotive markets. PAVS delivers best-in-class vertical software and co-engineered solutions that shorten design cycles for lighthouse customers while improving solution quality and user experience. THE ROLE: This position offers an exciting opportunity to work on the cutting edge of Physical AI solutions. As a senior technical contributor, you will play a key role in driving end-to-end delivery of customer robotics software solutions. Your responsibilities will include defining customer reference architectures, contributing to solution design, and coordinating implementation and optimization across multiple teams.

1. Based on customer scenarios, combine and configure various cloud products to create deployable solutions. 2. Continuously analyze the effectiveness of the solutions, attend to user feedback, identify and abstract typical issues, and continuously optimize the solutions to enhance user experience. 3. Participate in the project management of solution development, collaborating with product managers, R&D engineers, test engineers, interaction designers, product operations, and others to drive project implementation.

• Lead presales and architecture engagements with AI industry customers, focusing on GPU servers, AI clusters, and large‑scale training/inference platforms built on NVIDIA HGX, GPU systems, and reference architectures. • Design and validate end‑to‑end AI data center solutions, including server platforms, storage connectivity, and high‑performance networking based on Spectrum, Quantum, ConnectX, and BlueField. • Define system architectures for AI supercomputing, LLM training, and inference workloads, including node configuration, GPU topology, PCIe/NVLink considerations, and network design. • Support business teams in exploring, developing, and deploying NVIDIA server and GPU solution opportunities, from early technical discovery through POC and production rollout. • Own and execute POCs and hands‑on labs that validate GPU server performance, scalability, reliability, and interoperability across compute, storage, and network domains. • Troubleshoot complex end‑to‑end issues involving GPU servers, firmware, drivers, operating systems, and networking stacks, and drive fixes with internal R&D and partners. • Provide structured feedback on platform features, system requirements, and customer needs to server OEMs, engineering, and product teams to improve NVIDIA AI platforms and ecosystems.

• Lead hands-on design and development efforts primarily using Python, building robust, scalable, and customer-focused AI/ML solutions. • Engage directly with key enterprise customers to strategize, architect and implement AI driven, Agentic AI solutions leveraging Azure AI services including Azure OpenAI, Azure ML. • Translate complex requirements into practical, well-architected technical solutions. • Develop end-to-end, rapid prototypes, involving data ingestion, validation, processing, and model deployment using Azure platform components. • Build, customize, and optimize AI models and related components for customer-specific use cases. • Integrate AI solutions with full-stack architectures, preferably leveraging experience with JavaScript frameworks (e.g., Node.js, React) and/or .NET ecosystems. • Establish and maintain robust CI/CD and ML Ops pipelines, leveraging Azure DevOps, Github for automated deployments. • Proactively explore diverse datasets to engineer novel features and signals that significantly enhance ML performance. • Participate actively in every phase of the model lifecycle from conceptualization, training, fine tuning, validation, and deployment, to continuous monitoring and improvement.