Senior Principal Engineer - AI & HPC Solutions Architect

Role overview

Responsibilities

• Design scalable AI/HPC infrastructure for training and inference, including GPU clusters with thousands to tens of thousands of accelerators.
• Lead architecture, implementation, deployment, and optimization using NVIDIA, AMD, Intel, Base Command Manager, Slurm, Kubernetes, and related technologies.
• Direct benchmarking, validation, performance engineering, and scalability testing with tools such as NCCL, HPL, MLPerf, and IO500.
• Advise on AI factory architecture, platform engineering, scalability, operational strategy, roadmaps, and deployment plans.
• Resolve complex performance, scalability, and integration issues across compute, storage, networking, and software.
• Lead and mentor technical teams; create architecture diagrams, deployment guides, technical designs, and operational procedures.
• Serve as senior technical authority and trusted advisor during strategic customer engagements.

Essential requirements

• Proven success designing and deploying large-scale HPC and AI clusters using NVIDIA, AMD, and Intel technologies, including GPU environments with thousands of accelerators.
• Strong Linux systems administration, troubleshooting, and automation experience; extensive hands-on experience with Base Command Manager, Slurm, Kubernetes, or equivalent orchestration platforms.
• Deep high-performance networking expertise, including InfiniBand and RoCE; extensive benchmarking, scalability testing, validation, and optimization experience.
• Experience leading complex customer engagements and technical workstreams; strong customer-facing communication, consulting, and technical leadership skills.
• Ability to manage multiple large-scale projects and influence technical decisions across diverse stakeholder groups.

Desirable requirements

• Experience with NVIDIA DGX, DGX SuperPOD, AI Factory architectures, AI/ML and generative AI infrastructure, or large-scale LLM training and inference.
• Experience supporting GPU deployments with tens of thousands of accelerators.
• Python, Ansible, Terraform, or similar automation experience; knowledge of data center design, networking, storage, or cloud integration.
• Experience mentoring architects and leading technical teams across complex infrastructure programs.