Job Title: AI Engineering Lead, Automation and Platforms
Posting Start Date: 09/06/2026
Job Description
Key Responsibilities
- 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.
- 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.
- 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.
- 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.
- 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