Director of AI Infrastructure

Work Location: Hanoi: TechnoPark Tower, Vinhomes Ocean Park, Hanoi, Vietnam

Job overview:

We are investing in hyperscale AI infrastructure, with a long-term vision to develop multi-GW AI data center capacity and large-scale GPU compute clusters, enabling frontier model training and AI deployment at national scale.

We are looking for a Director of AI Infrastructure to architect, build, and scale our end-to-end AI infrastructure stack - from data center design to distributed training and inference systems.

This is a founding leadership role with full ownership of architecture, technology decisions, and ecosystem partnerships to build one of the largest AI infrastructure platforms in Southeast Asia.

Define and design the full stack of AI infrastructure:

→ Hyperscale data centers (multi-MW → GW-scale roadmap)

→ GPU clusters (hundreds → thousands GPUs, scaling toward 10,000+)

→ High-performance networking and distributed storage

Architect systems for frontier-scale model training and large-scale inference

2. Hyperscale Compute & Distributed Systems

• Build and operate large-scale GPU clusters (Phase 1: 500–1000 GPUs, scaling beyond)
• Design distributed systems for training, scheduling, and orchestration
• Optimize throughput, latency, utilization, and cost efficiency

3. AI Platform & Inference Systems

• Lead development of training and inference platforms
• Design systems for serving AI models at scale (millions of users / requests)
• Optimize model deployment, performance, and reliability

4. Data Center Strategy & Execution

• Lead design and scaling of AI-ready data centers (tens of MW → multi-GW roadmap)
• Drive decisions on power density, cooling (liquid/air), and rack design
• Own vendor ecosystem across NVIDIA, OEMs, networking, and infrastructure partners

5. Build the Team & Ecosystem

• Build and lead a world-class AI infrastructure organization
• Define engineering culture, hiring standards, and execution model
• Establish partnerships with global leaders in AI, cloud, and hardware ecosystems

What we are looking for:

We are open to candidates from different backgrounds, as long as you have built systems at scale in at least one of the following:

Option A - Distributed AI / Compute

• Built or operated large-scale distributed training systems
• Deep expertise in GPU clusters, HPC, or AI compute infrastructure

Option B - AI Platform / Inference

• Built AI platforms or large-scale inference systems
• Strong understanding of LLMs, training pipelines, and model optimization

Option C - Data Center / Hardware Infrastructure

• Designed or operated hyperscale data centers (MW-scale or beyond)
• Strong expertise in power, cooling, and high-density compute systems.

You might be a fit if you have:

• Experience working with hundreds → thousands → tens of thousands of GPUs
• Built systems for frontier AI / hyperscale cloud / HPC environments
• Strong hands-on technical depth combined with leadership and builder mindset