Head of Platform Engineering

Mars Consulting; Singapore; Sur place; SGD 180 000 - 300 000; Plein temps

Résumé du poste

Mars Consulting is seeking an experienced Head of Platform Engineering in Singapore to lead the client’s AI infrastructure, driving real-time inference services and cloud systems.

You will oversee GPU resources, model deployment, and production reliability, ensuring scalable, low-latency operations across the AI platform and collaborating with engineering teams to support growth.

Qualifications

• Proven experience in platform engineering, infrastructure, or distributed systems.
• Strong background building large-scale, low-latency systems.
• Experience with AI inference, GPU infra, and production deployment.
• Knowledge of reliability, monitoring, and performance optimization.

Responsabilités

• Lead development and management of AI infrastructure, including real-time inference services and cloud systems.
• Manage GPU resources and AI model deployment at scale.
• Optimize system performance and response times across the voice AI pipeline.

Connaissances

Platform engineering

Distributed systems

AI infrastructure

GPU infrastructure

SLOs & incident management

Leadership

Description du poste

Hiring!!

Position: Head of Platform Engineering

Location: Singapore

We are hiring an experienced Head of Platform Engineering to lead our client's AI infrastructure.

Key Responsibilities

• Lead the development and management of AI infrastructure, including real-time inference services and cloud systems.
• Manage GPU resources, computing capacity, and AI model deployment.
• Optimize system performance and response times across the entire voice AI pipeline.
• Ensure system reliability, availability, and scalability in production environments.
• Establish monitoring, incident response, and on-call engineering processes.
• Optimize infrastructure performance and operating costs.
• Lead and collaborate with engineering teams to support the company's growing AI platform.

Requirements

• Strong experience in platform engineering, infrastructure, or distributed systems.
• Proven experience building large-scale, low-latency, high-concurrency systems.
• Experience with AI model inference, GPU infrastructure, and production deployment.
• Strong knowledge of system reliability, monitoring, and performance optimization.
• Experience establishing SLOs and managing production incidents is highly preferred.
• Strong hands‑on engineering capabilities, with experience leading technical teams.