ICT Infrastructure Engineer (AI Platform) – Financial Regulatory Sector

About the Role

Our client is a prominent statutory authority in Singapore's financial sector, operating at the intersection of regulation, technology, and data. This role sits within a Production Engineering team that is responsible for deploying and managing enterprise-grade AI and data science platforms across both on-premises and cloud environments. You will serve as the technical bridge between data science, product management, and infrastructure teams — ensuring that AI products are reliably productionised and hosted at scale. This is a high-impact position for someone who thrives in a structured yet innovative environment and wants to shape how AI infrastructure is built and governed within a mission-critical organisation.

Key Responsibilities

• Lead the design, deployment, and configuration of resilient, secure, and scalable AI infrastructure in partnership with service providers and internal technology teams

• Drive the translation of business and compliance requirements into robust platform infrastructure designs that meet availability, reliability, and resilience standards

• Own the end-to-end onboarding of hosting environments, covering setup, configuration, implementation, testing, and commissioning of required infrastructure

• Act as the primary point of contact for new AI product initiatives, supporting system design, integration, and acceptance and performance testing

• Manage day-to-day AI platform operations, addressing queries from data scientists and product managers while maintaining service quality

• Develop and continuously improve operational runbooks, standard operating procedures, and automation scripts to simplify platform management and reduce manual effort

• Implement new platform features and enhancements to improve the overall AI development experience, including building reusable services and MLOps/LLMOps pipelines

• Collaborate with architecture, cybersecurity, and data platform teams to ensure all AI infrastructure aligns with enterprise architecture standards, security policies, and relevant regulatory frameworks

Requirements

• Hands-on experience building, securing, and operating enterprise Data Science and AI platforms on AWS or in on-premises environments, with a strong understanding of AI, application, and infrastructure security risks and controls

• Demonstrated experience designing and operating DevSecOps, MLOps, and/or LLMOps pipelines in production settings

• Proficiency with AI and container services, LLM inference, and Linux system administration; experience with Infrastructure-as-Code, automation tooling, and Python (is a bonus)