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Senior Director, AI Architecture

DayOne · Remote, Singapore

Data Science / AI / Machine LearningRemoteExternal listingfull-timeabout 2 hours ago

About The Role

Join DayOne – Shaping the Future of Data Infrastructure

DayOne is a global leader in the development and operation of high-performance data centers. As one of the fastest-growing companies in the industry, we’ve built a robust presence across Asia and Europe — and we’re just getting started.

As we expand into new international markets, we’re looking for talented, driven individuals to join us on this exciting journey. This is more than a job — it’s an opportunity to be a key contributor to our dynamic team and help shape the future of global data infrastructure.

If you're passionate about innovation, technology, and growth, we invite you to be part of DayOne’s next chapter.

Position Summary

The Senior Director, AI Infrastructure Architecture is DayOne’s senior technical authority for the architecture of AI-ready DC platforms. The role defines how compute, high-performance network fabrics, storage, fibre, power, cooling and physical deployment systems integrate into scalable AI POD and AI Factory solutions.

Building on the Network Systems Advisor remit, this permanent leadership role combines customer and OEM engagement, reference architecture, ecosystem development and organizational capability building. It enables DayOne to make credible customer commitments and develop repeatable platforms for high-density AI training and inference workloads, while partnering with Design and Operations teams that retain accountability for facility delivery and operation.

Key Accountabilities

  • AI platform architecture: Define end-to-end reference architectures for modular AI PODs and AI Factory deployments, integrating GPU/accelerator compute, scale-up and scale-out fabrics, high-performance storage, external connectivity and management networks.
  • Network and optical architecture: Set topology, performance, resilience, routing, oversubscription, addressing, structured cabling and optical design principles across InfiniBand, Ethernet/RoCE and emerging ultra-high-speed technologies.
  • Compute and storage integration: Define infrastructure requirements for GPU clusters, host platforms, NVMe-oF and parallel storage, ensuring data paths and capacity models support training and inference performance.
  • Physical infrastructure integration: Partner with facility engineering to align rack layouts, fibre pathways, containment, power density, liquid cooling, controls, maintainability and commissioning with AI system requirements.
  • Customer and OEM engagement: Lead technical discovery and architecture workshops with customers, GPU and server OEMs, network vendors, storage providers and integration partners; translate requirements into deployable specifications.
  • Pre-contract technical assurance: Support sales and investment decisions with solution options, assumptions, indicative configurations, delivery constraints, cost drivers and technical risk assessments.
  • Standards and playbooks: Create governed reference designs, interface standards, requirements templates, deployment patterns and acceptance criteria that can be reused across markets and customer programmes.
  • Partner ecosystem: Shape preferred partner frameworks and technical evaluation criteria for compute, storage, networking, optics, fibre and system integration suppliers.
  • Capability and operating model: Assess organizational capability, define specialist roles and build the architecture, network engineering, fibre delivery and validation capabilities required to scale.
  • Technology roadmap: Track and evaluate emerging AI infrastructure technologies, balancing innovation with interoperability, supply chain, lifecycle, security and operational readiness.
  • Technical governance: Chair AI architecture reviews, maintain architecture decision records and provide expert escalation for cross-layer performance, interoperability and deployment risk.

Qualifications & Experience

  • Degree in Computer Engineering, Electrical Engineering, Network Engineering or a related technical discipline; advanced degree advantageous.
  • Typically 15+ years in data centre network, high-performance computing, cloud infrastructure or AI infrastructure architecture, with senior technical leadership responsibility.
  • Deep expertise in high-radix Clos fabrics, InfiniBand and Ethernet/RoCE architectures, routing, optics, structured fibre and high-density physical deployment.
  • Strong understanding of GPU cluster architecture, high-performance storage, workload data flows and the power/cooling implications of AI platforms.
  • Proven experience defining reference architectures and converting customer/OEM requirements into buildable deployment specifications.
  • Track record of vendor evaluation, partner ecosystem development and influencing executive investment decisions.

Success Measures

  • Approved, reusable AI POD and AI Factory reference architectures with clear performance and interface requirements.
  • Reduced solution cycle time and technical risk in AI-related pursuits and deployments.
  • Validated integration across compute, storage, network, fibre, power and cooling domains.
  • Strong OEM/customer confidence and improved quality of pre-contract technical commitments.
  • Qualified partner ecosystem and measurable improvements in deployment readiness and repeatability.
  • Development of sustainable internal architecture, fibre engineering and validation capability.
  • DayOne is proud to be an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
  • If you're ready to grow with one of the fastest-moving companies in the data center industry, apply now and be part of our global journey.

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