Principal Architect - AI

• Lead the end-to-end architecture of GPU-accelerated HPC and AI platforms, including greenfield AI factory designs and optimization of existing HPC environments. 

• Architect integrated solutions spanning Compute, Networking, and Storage using NVIDIA HGX and DGX platforms, Grace CPU architectures, Spectrum-X networking, and high-performance parallel storage systems. 

• Design storage architectures optimized for AI training, inference, and HPC workloads, balancing performance, scalability, resiliency, and cost. 

• Define reference architectures, design patterns, and best practices for repeatable and supportable customer deployments. 

• Provide hands-on technical leadership during implementation phases, including cluster bring-up, performance tuning, and workload optimization. 

• Architect and integrate workload orchestration and scheduling platforms using NVIDIA Base Command Manager, Slurm, Kubernetes and Run:AI. 

• Optimize end-to-end data pipelines, including GPU utilization, storage throughput, metadata performance, and job scheduling efficiency. 

• Troubleshoot performance bottlenecks across Compute, Networking, and Storage. 

• Design and validate high-performance storage solutions using modern parallel and scale-out storage platforms. 

• Demonstrate hands-on experience with at least one of the following storage technologies 

• VAST Data 

• WEKA 

• DDN 

• Lustre 

• NetApp 

• Architect storage solutions that support demanding AI and HPC workloads, including high-throughput training pipelines, checkpointing, and large-scale shared datasets. 

• Collaborate with compute and networking design to ensure balanced, bottleneck-free architectures. 

• Act as a senior technical authority for HPC and AI architecture across internal teams and customer engagements. 

• Participate selectively in customer-facing discussions to validate architecture and delivery plans, with a primary focus on design integrity and execution rather than pre-sales. 

• Influence platform standards, architectural direction, and technical decision-making through expertise and demonstrated execution. 

• Identify technical risks early across Compute, Networking, Storage, and orchestration layers, and drive mitigation strategies.  

• Partner with the PMO counterpart to resolve Risks and Issues upon identification and to ensure production-ready, supportable platforms. 

• Ensure staff, contractors, and partners adhere to best practices and templates for AI solution delivery. 

• Review deployment documents, technical assessments, and other outputs to ensure consistency and accuracy, aligning with AI and "One Voice" standards. 

• Expert level with deep architectural knowledge of NVIDIA data center platforms, including HGX and DGX platforms. 

• GPU-accelerated compute architecture for AI and HPC workloads. 

• High-performance networking architectures, especially with Spectrum-X. 

• Large-scale AI factory and HPC platform design. 

• Hands-on architectural experience with high-performance parallel or scale-out storage systems. 

• Deep understanding of storage performance characteristics relevant to AI and HPC workloads, including bandwidth, IOPS, latency, and metadata scaling. 

• Proven experience integrating storage platforms such as VAST Data, NetApp, WEKA, DDN, or Lustre into GPU-accelerated environments. 

• NVIDIA Base Command Manager (BCM) for cluster lifecycle management and operations. 

• Slurm for HPC workload scheduling and resource management. 

• Run:AI for GPU orchestration and multi-tenant AI workload optimization. 

• Kubernetes administration including deploying and managing GPU-accelerated AI and HPC workloads. 

• Linux systems administration in large-scale, performance-sensitive environments. 

• Containerized AI workflows and their interaction with schedulers and storage systems. 

• Experience optimizing existing HPC or AI platforms for performance, utilization, and cost efficiency. 

• Prior experience with multi-site, air-gapped, or regulated environments is beneficial but not required. 

• Experience with liquid cooling, power/cooling design, and data center integration strongly preferred. 

• Senior individual contributor role with influence through technical authority rather than people management. 

• Ability to mentor engineers and architects through design reviews, architectural guidance, and technical leadership. 

• Comfortable operating autonomously in complex, high-impact technical environments. 

• Develop and maintain high quality architectural documentation, including design blueprints, configuration guides, deployment validation reports, and operational runbooks. 

• Ensure all technical artifacts meet One Voice standards for clarity, completeness, and technical accuracy, enabling consistent delivery across teams. 

• Create reusable templates, reference architectures, and standardized design patterns that accelerate future projects and improve delivery quality. 

• Drive a culture of documentation discipline, ensuring that every deployment is reproducible, supportable, and aligned with architectural intent. 

• Bachelor’s degree in a technical field or equivalent hands-on experience architecting large scale HPC or AI systems on experience architecting large scale HPC or AI systems. 

• Advanced degree (MS/PhD) in relevant fields is a plus but not required. 

• Experience: 10+ years in HPC, Data Center Architecture, and/or Systems Engineering. 

• Bare Metal Focus: A fundamental preference for, and understanding of, on-premises hardware constraints (power, cooling, cabling). 

• Proven experience as a Senior, or Lead Architect or equivalent experience in AI projects. 

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