AI Data Center Architect

We are seeking an experienced AI Data Center Architect to design, architect, and lead the implementation of next-generation AI infrastructure and AI Factory environments. The ideal candidate will have strong expertise in GPU-based computing, NVIDIA Reference Architecture, GPUaaS, accelerated computing, AI cloud platforms, and large-scale data center infrastructure.

The architect will be responsible for developing scalable, high-performance, and reliable infrastructure for Generative AI, Large Language Models (LLM), machine learning, and enterprise AI workloads.

The role requires hands-on architectural experience with NVIDIA DGX, HGX, Blackwell, GB200, Spectrum-X, InfiniBand, and GPU cloud infrastructure., AI Infrastructure & Data Center Architecture

• Design end-to-end AI Data Center and AI Factory architectures for large-scale GPU workloads.
• Develop infrastructure blueprints for AI training, inference, and accelerated computing environments.
• Architect scalable GPU clusters, compute, networking, storage, and data center infrastructure.
• Evaluate infrastructure requirements for LLM, GenAI, and enterprise AI platforms.
• Design high-availability, scalable, and performance-optimized AI infrastructure solutions.
• Define infrastructure standards, reference designs, and architecture best practices.

NVIDIA AI Infrastructure

• Design and implement NVIDIA-based AI infrastructure using NVIDIA Reference Architecture.
• Architect NVIDIA DGX and HGX platforms for enterprise AI and large-scale GPU computing.
• Experience with NVIDIA Blackwell architecture and GB200 systems.
• Design GPU clusters and accelerated computing platforms for AI workloads.
• Evaluate NVIDIA GPU, CPU, networking, storage, and software stack requirements.
• Collaborate with hardware, cloud, network, and data center engineering teams.

GPUaaS & AI Cloud

• Architect GPU-as-a-Service (GPUaaS) and GPU Cloud platforms.
• Design multi-tenant GPU infrastructure and resource allocation models.
• Develop scalable AI Cloud and GenAI platform architectures.
• Support GPU provisioning, scheduling, monitoring, and capacity planning.
• Define infrastructure requirements for AI model training, inference, and deployment.
• Evaluate cloud and on-premises GPU infrastructure solutions.

High-Performance Networking

• Architect high-performance networking for AI GPU clusters.
• Strong experience with NVIDIA Spectrum-X networking and InfiniBand.
• Design low-latency, high-bandwidth network architectures for distributed AI workloads.
• Evaluate RDMA, RoCE, InfiniBand, Ethernet, and GPU interconnect technologies.
• Support network scalability, performance optimization, and troubleshooting.
• Collaborate with network engineering teams on AI data center deployments.

AI Platform & LLM Infrastructure

• Design infrastructure platforms supporting Generative AI and LLM workloads.
• Define compute, GPU, storage, networking, and orchestration requirements.
• Support AI model training, fine-tuning, inference, and serving environments.
• Collaborate with AI/ML engineers, platform engineers, DevOps, and cloud architects.
• Evaluate containerized AI infrastructure, Kubernetes, and GPU orchestration platforms.
• Develop infrastructure strategies for enterprise AI and AI cloud environments.

Architecture Governance & Delivery

• Create High-Level Design (HLD), Low-Level Design (LLD), architecture diagrams, and technical documentation.
• Lead architecture reviews, technology evaluations, and infrastructure design workshops.
• Define capacity planning, performance, availability, scalability, and security requirements.
• Support proof of concepts, infrastructure deployment, and production readiness.
• Work with vendors and technology partners on infrastructure solutions.
• Provide technical leadership and guidance to infrastructure engineering teams.

Experience: 10+ years in Data Center, Cloud Infrastructure, HPC, or AI Infrastructure Architecture, * 10+ years of experience in Data Center Architecture, Cloud Infrastructure, HPC, or AI Infrastructure.

• Strong experience designing AI Factory or AI Data Center environments.
• Expertise in NVIDIA Reference Architecture.
• Hands-on architecture experience with NVIDIA DGX and HGX platforms.
• Experience with NVIDIA Blackwell architecture and GB200 systems.
• Strong knowledge of GPUaaS, GPU Cloud, and AI Cloud infrastructure.
• Expertise in AI Infrastructure and Accelerated Computing.
• Experience with NVIDIA Spectrum-X and InfiniBand networking.
• Strong understanding of LLM Infrastructure and GenAI Platform architecture.
• Experience designing scalable GPU clusters and distributed AI environments.
• Strong knowledge of data center compute, networking, storage, and infrastructure architecture.

Preferred Qualifications

• Experience with NVIDIA AI Enterprise and AI software ecosystems.
• Experience with Kubernetes, GPU orchestration, and containerized AI platforms.
• Knowledge of RDMA, RoCE, NVLink, and high-performance GPU interconnects.
• Experience with AI infrastructure monitoring, automation, and observability.
• Experience with enterprise AI cloud or hyperscale data center environments.
• Knowledge of power, cooling, rack density, and physical data center requirements.
• NVIDIA certifications or relevant cloud/data center architecture certifications.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.