概要

• 給与

  9,000 SGD ~ 13,000 SGD

• 業界

  IT/Telecommunications

• 仕事内容

  Our client designs, develops, and supplies hardware, software, and integrated solutions for applications in payment, self-service operations, and environmental management. They are currently seeking an experienced Director, AI Engineering & Software Development to lead the development and operational adoption of AI-enabled software engineering practices, drive continuous innovation, and oversee the delivery of scalable, high-quality products and services across regional engineering teams.
  
  Report line: CIO
  
  【 Responsibilities 】
  
  1. Continuous Innovation & Technology Development
  - Establish mechanisms for continuous improvement by regularly evaluating advancements in frontier AI models, open-source libraries, AI-assisted development tools, and advanced coding frameworks.
  - Serve as the squad's technology leader by monitoring developments across the global software engineering community and rapidly evaluating, adapting, and implementing relevant industry practices within active delivery pipelines.
  - Design and optimise operational workflows that enable multiple independent AI-assisted development streams to operate efficiently within a single squad while minimising delivery friction and integration bottlenecks.
  
  2. Strategic Leadership & Regional Team Management
  - Lead, mentor, and develop a regional engineering and product delivery team, fostering effective collaboration across geographically distributed teams.
  - Drive the adoption of AI-assisted software development practices, including continuous tool experimentation, prompt refinement, and automated system orchestration.
  - Foster a collaborative and inclusive working environment that integrates diverse perspectives and supports delivery efficiency and alignment with product objectives.
  
  3. Process Optimisation & Git Workflow Governance
  - Drive the adoption and continuous enhancement of Specification-Driven Development (SDD), ensuring machine-readable specifications, including API schemas and custom Agent Manifests, support consistent and reliable autonomous execution.
  - Establish and enhance multi-agent code merging and validation processes integrated with enterprise Git workflows, including branching strategies, automated pull-request reviews, code conflict resolution, and semantic versioning.
  - Ensure parallel AI-assisted development streams are effectively integrated into core deployment pipelines while maintaining code quality, structural integrity, and release standards.
  
  4. Governance, Security & Guardrails
  - Design and continuously improve enterprise-grade governance frameworks for managing AI agent autonomy, establishing appropriate controls for automated code generation, refactoring, and self-healing systems.
  - Establish risk mitigation protocols, cost monitoring mechanisms, and quality gates to support scalable AI-assisted development while minimising quality issues and unintended system behaviour.
  - Define and standardise Human-in-the-Loop (HITL) approval protocols, determining appropriate points for human intervention and levels of permitted AI agent autonomy.
  
  5. Process & Tool Innovation
  - Collaborate with internal platform teams to develop and integrate specialised tools that enhance the capabilities of AI agents, including Knowledge Agents for support, Automated Root Cause Analysis (RCA) agents, and proactive synthetic monitoring agents.
  - Analyse delivery data and squad performance metrics to identify opportunities for platform and process optimisation, incorporating insights from historical performance data and sprint retrospectives.
  - Provide accountability to the CIO for the quality, scalability, and timely delivery of products and services developed by the Agentic Squads.