AI Data Center Architect

About the role

We are looking for an experienced AI Data Center Architect to lead solution architecture, integration planning, and technical governance for a large‑scale, multi‑tenant AI infrastructure platform. The role bridges business objectives, AI and data‑platform requirements, and infrastructure capabilities to deliver a scalable, secure, and operable solution.

Key responsibilities

• Conduct requirements discovery and architecture workshops with business, IT, data, security, operations, and vendor stakeholders.
• Translate business, workload, security, performance, and availability requirements into high‑level designs, architecture principles, and implementation roadmaps.
• Define end‑to‑end architecture across GPU compute, networking, storage, management, security, automation, monitoring, platform services, and Day‑2 operations.
• Coordinate low‑level design development with domain architects and engineers, ensuring alignment with approved high‑level designs and technical standards.
• Maintain architecture decisions, assumptions, dependencies, technical risks, and design‑review records.
• Assess AI and data‑platform requirements and map training, inference, validation, and tenant workloads to appropriate infrastructure models.
• Design integration approaches across on‑premises data centers, private clouds, and public clouds, covering data flows, security boundaries, and operational dependencies.

Required profile

• Senior‑level professional with strong consulting and cross‑functional leadership experience.
• Proven ability to guide design decisions, identify dependencies and risks, and collaborate with specialists in GPU, networking, storage, and software.
• Experience working with hybrid environments (on‑premises, private cloud, public cloud) and multi‑tenant AI platforms.

Required skills

• GPU compute architecture
• Kubernetes orchestration
• Networking design
• Storage systems
• Automation frameworks
• Security and compliance
• Monitoring and observability
• Hybrid cloud infrastructure (on‑premises, private, public)
• Solution architecture and high‑level/low‑level design