AI Infrastructure Lead (AI Inference Platform)

AI Infrastructure Lead (AI Inference Platform)
Singapore | Permanent

About Our Client
Our client is a publicly listed AI compute and data centre infrastructure provider and an NVIDIA partner. It runs the latest generations of GPU clusters, from H100 to GB300, across North America, Europe and Asia. Its customers include frontier AI labs, hyperscalers and leading internet companies, which buy high-performance GPU compute and full-lifecycle data centre capacity.
As part of its APAC expansion, the company is building a new AI inference platform from Singapore and is hiring a founding technical leader to own it end to end.

Why This Role
You join at the ground floor and shape the architecture, tech stack and engineering culture from day one
You build and lead the Singapore engineering team
You work hands-on with large-scale, latest-generation GPU infrastructure
You work closely with the global infrastructure and engineering teams of a listed company

What You’ll Do
Architecture & Technical Direction
Own the end-to-end architecture of the platform, covering AI inference services, GPU infrastructure, backend systems and platform operations
Evaluate technology options and lead key technical decisions
Set engineering standards, documentation practices and architecture best practices
Reuse existing global infrastructure and engineering capabilities where it makes sense
Hands-on Engineering & Delivery
Stay hands-on in system development, infrastructure integration and complex problem-solving
Lead design reviews and resolve performance bottlenecks, scalability issues and technical risks
Drive delivery while balancing performance, reliability, security and infrastructure cost
Team Building
Hire, mentor and grow a high-performing engineering team
Define technical competency standards and lead technical interviews
Set up engineering workflows and code review standards, and build a culture of ownership and continuous improvement
Global Collaboration
Work with global infrastructure, engineering and business teams, and coordinate dependencies across them
Turn business objectives into technical priorities and execution plans
Communicate architecture decisions, progress and risks to stakeholders

What You Bring
8+ years in software engineering, distributed systems, cloud or AI infrastructure, including technical leadership experience
A track record of designing and delivering production-grade distributed systems or infrastructure platforms
Strong understanding of AI infrastructure, GPU computing and inference platform architecture
Hands-on experience with Linux, Kubernetes, containers and modern cloud infrastructure
Strong programming skills in Python, Go, C++ or a comparable language
Sound architectural judgement and the ability to assess engineering talent
Excellent English communication and experience working across global teams

Nice to Have
Experience building or operating AI inference platforms, GPU cloud or large-scale compute infrastructure
Familiarity with vLLM, TensorRT-LLM or SGLang
Knowledge of GPU resource scheduling, distributed inference, model serving and performance optimisation
Experience with platform reliability, observability and infrastructure automation
Experience building teams or platforms from an early stage
A background in AI infrastructure, cloud platforms, HPC or high-growth tech companies

All applications will be treated with strictest confidence. We regret to inform you that only shortlisted candidates will be notified.

EA Licence No: 19C9807

Registration No: R22110556 (ZHOU DONGYANG)