AI Engineering Lead, Automation and Platforms

Job Description

Key Responsibilities

1. Technical Architecture and Solution Design

• Define the technical architecture for AI automation, workflow automation, data integration and platform capabilities across ETP.
• Determine how the data lake, AI inference layer, vector database, workflow automation tools, SaaSplatforms and ETP Hub should connect.
• Translate business requirements and operational pain points into technical solution designs, delivery plansand prioritised build tasks.
• Ensure technical solutions are secure, maintainable, reusable and aligned with ETP's longer-term digital operating model.

2. AI Engineering Delivery Leadership

• Lead the AI Engineers in delivering AI agents, automation workflows, data pipelines, reporting automation and integration components.
• Review technical outputs including scripts, workflows, data logic, API integrations, AI-assisted tools and deployment approaches.
• Set delivery standards for code quality, testing, documentation, release readiness and post-launch sustainment.
• Support the use of AI coding tools to accelerate development while ensuring appropriate technical review and quality control.

3. Data, AI and Workflow Automation

• Provide technical oversight for data cleanup, data transformation, reconciliation logic, reporting automation and AI-enabled reporting.
• Guide the development of AI inference-layer capabilities for extraction, classification, validation,summarisation and report generation.
• Lead workflow automation approaches using tools such as n8n and related integration platforms.
• Guide AI-enabled features within ETP Hub, including search, knowledge retrieval, agent workflows and user-facing automation.

4. Platform, SaaS and Infrastructure Integration

• Ensure automation solutions integrate properly with ETP's platforms, SaaS applications, workflow tools, datasources and infrastructure.
• Work with platform, SaaS and infrastructure workstreams to align technical dependencies, implementation sequencing and support arrangements.
• Assess vendor and professional services proposals for technical soundness, scalability, maintainability and handover readiness.
• Surface risks, constraints and trade-offs early, including security, data access, infrastructure, integration and sustainment considerations.

5. Governance, Documentation and Sustainment

• Establish technical standards for automation workflows, data pipelines, scripts, AI agents, prompts,integrations and reusable components.
• Ensure documentation of architecture, data flows, business rules, workflow logic, prompts, APIs, dependencies and support arrangements.
• Put in place testing, monitoring and issue-resolution processes for deployed automation and AI-enabled tools.
• Drive continuous improvement based on user feedback, adoption, operational performance and changing business needs.

Qualifications

• Degree in Computer Science, Software Engineering, Data Science, Information Systems, Engineering or arelated technical discipline; equivalent practical experience may be considered.
• Typically 8 or more years of relevant experience in software engineering, AI engineering, data engineering,platform integration or digital solution delivery.
• At least 3 years of experience leading technical delivery, solution architecture, engineering teams or cross-functional automation workstreams.
• Strong hands-on understanding of Python or similar languages, APIs, data pipelines, system integration anddeployment practices.
• Practical experience with AI agents, LLM workflows, RAG, embeddings, vector databases, knowledgeretrieval or AI inference-layer design.
• Experience with workflow automation tools such as n8n, Airflow, Zapier, Make or similar platforms.
• Ability to guide engineers, review technical work, challenge vendors, make architecture decisions andtranslate business problems into scalable technical solutions.
• Strong communication and stakeholder management skills, with the ability to explain technical trade-offsclearly to both technical and non-technical stakeholders.

Good to Have

• Experience with AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot or similar tools.
• Experience with Google Workspace, Monday.com, Slack, Xero, Workable or similar SaaS applications.
• Experience building internal automation platforms, knowledge search tools, dashboards or operational applications.
• Familiarity with local or cloud-based AI infrastructure, data vectoring, RAG pipelines and knowledge retrieval systems.
• Experience in corporate services, operations, grants, finance, HR, administration or similar internal operating environments.

More Information

Job Type: 2-year Contract

Location: Kent Ridge Campus

Organization: NUS Enterprise

Department : ETP - Administration

Job requisition ID : 33261