AI Engineering & Platform Delivery Lead

National University Of Singapore; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

National University Of Singapore seeks a seasoned leader to architect AI automation and data platforms. You will guide AI engineers, manage data pipelines and ensure scalable, secure solutions across ETP initiatives. The role emphasizes architecture, governance and cross-team delivery.

You will lead delivery standards, review AI outputs, and champion scalable integration with SaaS platforms and data sources, while driving continuous improvement and stakeholder alignment.

Qualifications

• Degree in Computer Science, Software Engineering, Data Science or related field.
• Typically 8+ years in software/AI engineering, data integration or digital delivery.
• At least 3 years leading technical delivery and cross-functional teams.
• Strong Python, APIs, data pipelines, and system integration experience.
• Experience with AI agents, LLM workflows, embeddings, vector databases or AI inference design.

Responsibilities

• Define technical architecture for AI automation, data integration and platform capabilities.
• Lead AI Engineers delivering AI agents, automation workflows, and data pipelines.
• Guide data cleanup, transformation, reconciliation and AI-enabled reporting.
• Ensure secure, maintainable, reusable solutions aligned with the digital operating model.
• Governance, documentation and sustainment of automation and AI tools.

Skills

Technical leadership

Python

APIs & data pipelines

Stakeholder management

Systems integration

Problem solving

Education

Bachelor's or higher in CS/Engineering/Data Science

Tools

n8n

Airflow

Zapier

Make

Job description

National University Of Singapore seeks a seasoned leader to architect AI automation and data platforms. You will guide AI engineers, manage data pipelines and ensure scalable, secure solutions across ETP initiatives. The role emphasizes architecture, governance and cross-team delivery.

You will lead delivery standards, review AI outputs, and champion scalable integration with SaaS platforms and data sources, while driving continuous improvement and stakeholder alignment.