AI Engineer, AI Agents and Platform Integration

National University of Singapore; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

National University of Singapore seeks an AI Engineer to build AI agents, RAG/vector search components, and platform integrations to support ETP Hub and automation roadmaps. The role is hands-on, developing tools that reduce manual work and improve information retrieval across ETP systems.

The candidate will work under the AI Engineering Lead, focusing on testing, deployment, and sustainment of AI-enabled workflows with strong emphasis on practical tooling and documentation.

Qualifications

• Degree or diploma in Computer Science, Software Engineering, Data Science, Information Systems, Engineering or a related technical discipline; equivalent practical experience may be considered.

Responsibilities

• Build AI agents and AI-enabled features for ETP Hub and automation workflows.
• Develop RAG/vector search components and knowledge retrieval capabilities.
• Create API connectors and automation utilities for platform integrations.
• Develop reusable scripts and utilities for data cleanup, reporting, and knowledge retrieval.
• Test, deploy and sustain AI-enabled tools with clear documentation and handover artifacts.

Skills

Python

APIs

Scripting

Data processing

Automation

LLMs & AI agents

Workflow understanding

Education

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

Tools

FastAPI

Streamlit

LangChain

LlamaIndex

n8n

GitHub Copilot

Google Workspace

Job description

The AI Engineer will build AI agents, knowledge retrieval capabilities and platform integrations to support ETP Hub and ETP's automation roadmap. The role will develop practical AI-enabled tools that reduce manual work, improve search and retrieval, and connect AI capabilities with ETP's systems and workflows.

This is a hands-on builder role focused on developing, testing and sustaining AI agents, RAG/vector search components, API integrations and reusable automation utilities under the guidance of the AI Engineering Lead. The role will build AI agents, RAG/vector search solutions and platform integrations for ETP Hub and automation workflows.

Key Responsibilities

1. AI Agents and ETP Hub Features

• Build and enhance AI agents and AI-enabled features for ETP hub.
• Support use cases such as document search, summarisation, classification, task assistance and guided workflows.
• Develop user-facing tools that help staff retrieve information, generate outputs and complete administrative tasks more efficiently.
• Test and refine AI-enabled features based on user feedback and operational needs.

2. RAG, Vector Search and Knowledge Retrieval

• Support retrieval-augmented generation workflows using internal documents, datasets and system outputs.
• Build and maintain embeddings, vector search and knowledge retrieval components.
• Work with structured and unstructured information including documents, reports, spreadsheets, emails, datasets and system records.
• Support data preparation, chunking, indexing, retrieval testing and quality checks for knowledge search use cases.

3. Platform and Workflow Integration

• Build integrations between ETP Hub, workflow tools, data sources and SaaS applications.
• Develop scripts, API connectors and automation components to support system-to-system workflows.
• Work with internal users and vendors to test, troubleshoot and refine integrations.
• Support integration of AI capabilities into existing workflows and operational processes.

4. AI-Assisted Development and Reusable Utilities

• Use AI coding tools such as Claude Code, Cursor or GitHub Copilot to accelerate development.
• Build reusable scripts, templates and utilities for data cleanup, reporting support, knowledge retrieval and automation.
• Provide practical scripts or tools that can be used by internal teams where appropriate.
• Document prompts, scripts, workflows, APIs, dependencies and support steps clearly.

5. Testing, Deployment and Sustainment

• Test AI agents, integrations and automation components before deployment.
• Support troubleshooting, refinements and post-launch enhancements.
• Monitor issues, performance and user feedback for deployed AI-enabled tools.
• Maintain clear documentation for handover, support and future enhancement.

Please be informed that only shortlisted candidates will be notified.

Qualifications

• Degree or diploma in Computer Science, Software Engineering, Data Science, Information Systems, Engineering or a related technical discipline; equivalent practical experience may be considered.
• Typically 3 to 5 years of hands-on experience in AI engineering, software engineering, data engineering, system integration or automation development.
• Hands-on experience with Python, APIs, scripting, data processing and automation.
• Familiarity with LLMs, AI agents, RAG, embeddings, vector databases or AI workflow tools.
• Able to build practical internal tools, automation scripts and user-facing AI-enabled features.
• Comfortable using AI-assisted coding tools such as Claude Code, Cursor, GitHub Copilot or similar tools.
• Able to work with users to understand workflow pain points and translate them into working technical solutions.
• Good testing, documentation and troubleshooting discipline.

Good to Have

• Experience with n8n, LangChain, LlamaIndex, FastAPI, Streamlit, Next.js or similar tools.
• Experience with Google Workspace, Slack, Monday.com, Xero, Workable or other SaaS platforms.
• Experience building internal knowledge search, chatbot, workflow or reporting tools.
• Familiarity with local or cloud-based AI infrastructure, vector databases and RAG pipelines.
• Experience supporting operational, administration, finance, HR, grant or reporting workflows.