Role: Senior Cloud Architect - GPU Infrastructure & AI Platforms

Function: Cloud Infrastructure & Platform Engineering

Location: Singapore

Type: Full-time

Compensation: Not specified

Industry: Information Technology & Services

About Company

A deeptech startup building the next generation of AI-native infrastructure. As a Zero-Trust and Confidential-by-Design hyperscaler, we are developing the Kluisz Secure Fabric™️ to redefine how the world handles massive-scale compute.

We are looking for a visionary Senior Cloud Architect to lead the design, deployment, and operation of our large-scale GPU cloud infrastructure in Singapore. You will own the end-to-end GPU platform architecture—from hardware and cluster design to Kubernetes scheduling and customer solutioning.

Position Overview

You will architect and deploy 2,000+ GPU clusters that power the next generation of AI infrastructure. You own the end-to-end GPU platform architecture, bridging specialized hardware teams and AI engineers to deliver production-ready cloud solutions. This role defines the technical direction of a hyperscaler fleet from the ground up, with high ownership and direct impact on global cloud infrastructure.

Role & Responsibilities

• Design and evolve large-scale GPU clusters (2,000+ GPUs) for AI training and inference workloads
• Define GPU server topology including PCIe/NVLink configurations and high-speed networking architecture
• Architect and oversee Kubernetes-based GPU platforms with scheduling, isolation, and multi-tenant strategies
• Support deployment and optimization of AI models while troubleshooting complex distributed training issues
• Evaluate and select GPU, server, and networking vendors with technical input for RFPs
• Lead customer engagements for solution architecture and provide technical leadership
• Mentor infrastructure and platform engineers while driving capacity planning initiatives

Must Have Criteria

• 10-15 years of experience in cloud infrastructure, platform engineering, or systems architecture
• Proven experience designing or operating GPU clusters with at least 2,000 GPUs
• Strong production experience with Kubernetes specifically for GPU workloads and resource scheduling
• Deep understanding of GPU architecture and compute optimization across different GPU vendors
• Experience with high-performance networking protocols (InfiniBand or RoCE) for GPU clusters
• Hands-on experience with distributed storage systems optimized for AI workloads
• Experience in customer-facing solution architecture or technical leadership roles

Nice to Have

• Experience with AI/ML frameworks and large-scale training platforms (PyTorch, TensorFlow)
• Exposure to multi-cloud or hybrid cloud environments
• Track record of improving GPU utilization and cost efficiency at scale
• Experience with container orchestration tools beyond Kubernetes (Docker Swarm, Nomad)
• Background in hyperscaler or cloud service provider environments

What We Offer

• Opportunity to build next-generation AI infrastructure from the ground up
• Leadership role in a cutting-edge Zero-Trust and Confidential-by-Design hyperscaler
• Work with state-of-the-art GPU technology and secure fabric architecture
• High ownership and impact in shaping global cloud infrastructure
• Collaborative environment focused on redefining massive-scale compute