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Kerja Sepenuh Masa, AI Infrastructure Lead( Engineering) di Trulyyy - Maukerja

AI Infrastructure Lead( Engineering)

Trulyyy

Singapore

Kongsi
Simpan

Lokasi Kerja

  • Singapore

Penerangan Kerja

Tanggungjawab

We are partnering with a fast-growing AI Cloud & GPU Infrastructure company to hire a hands-on AI Infrastructure Lead based in Singapore.

The company is building next-generation AI computing infrastructure, supporting the growing demand for large-scale AI workloads and high-performance computing.

  • Cutting-Edge AI Infrastructure: Work with advanced NVIDIA GPU technologies and large-scale AI computing environments.
  • Build from 0 to 1: Take ownership of a new GPU Cloud & AI Inference Platform, shaping its architecture and technical direction from the ground up.
  • High-Impact Leadership: Play a key role in technical decision-making, engineering execution, and building the core engineering team.
  • Hands-on Technical Ownership: Stay close to architecture and coding while leading the development of scalable, high-performance infrastructure systems.


Responsibilities

  • Lead the architecture, design, and development of scalable AI infrastructure and cloud-based platforms.
  • Drive technical decisions and deliver reliable, high-performance distributed systems.
  • Provide hands-on engineering leadership in software development, system integration, and performance optimization.
  • Design and optimize infrastructure solutions supporting GPU computing and AI workloads.
  • Establish engineering best practices, conduct code reviews, and maintain high development standards.
  • Build and mentor engineering teams, providing technical guidance and supporting recruitment.
  • Collaborate with cross-functional teams to translate business requirements into technical solutions and drive project delivery.


Requirements

  • 8+ years of experience in software engineering, cloud platforms, or infrastructure development, with exposure to technical leadership.
  • Strong background in designing and building scalable, high-performance distributed systems.
  • Solid understanding of GPU computing, cloud architecture, and infrastructure supporting AI workloads.
  • Hands-on experience with Kubernetes, Linux, and containerized environments.
  • Proficiency in at least one programming language, such as Go, Python, or C++.
  • Ability to drive technical decisions, solve complex engineering challenges, and deliver production-ready solutions.
  • Strong communication skills and experience working with cross-functional teams.



Preferred Qualifications

  • Experience developing GPU-based cloud platforms, AI infrastructure, or large-scale computing systems.
  • Exposure to LLM deployment, model serving, or inference technologies.
  • Knowledge of GPU resource management, workload scheduling, and distributed computing.
  • Familiarity with infrastructure automation, system monitoring, and performance optimization.
  • Previous experience mentoring engineers or leading technical projects in a growing engineering environment.





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