NUS Enterprise

Higher Education

AIEngineer,AIAgentsandPlatformIntegration

S$80–130k ~AI est. Singapore, Singapore, Singapore CONTRACT
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“AI Engineer, AI Agents and Platform Integration at NUS Enterprise. Skills: AI agents, RAG, Platform integration, Automation. Build and enhance AI agents and AI-enabled features. Support use cases such as document search, summarisation,”

Industry & Context.

Higher Education
Problems you'll solve

Troubleshooting; Workflow pain points translation

What They're Looking For.

Must Have

Degree or diploma in Computer Science, Software Engineering, Data Science, Information Systems, Engineering or related, 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, Able to build practical internal tools, automation scripts and user-facing AI-enabled features, Able to work with users to understand workflow pain points and translate them into working technical solutions, Good testing, documentation and troubleshooting discipline

Nice 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

What You'll Do.

Build and enhance AI agents and AI-enabled features

Support use cases such as document search

Develop user-facing tools to retrieve information

Test and refine AI-enabled features based on user

Support retrieval-augmented generation workflows using internal documents

Build and maintain embeddings

vector search and knowledge

Work with structured and unstructured information

Support data preparation

retrieval testing and

Build integrations between ETP Hub

API connectors and automation components

Work with internal users and vendors to test

Support integration of AI capabilities into existing workflows

Use AI coding tools to accelerate development

Build reusable scripts

templates and utilities for data

Provide practical scripts or tools for internal teams

dependencies and support

integrations and automation components before

Support troubleshooting

refinements and post-launch enhancements

performance and user feedback for deployed

Maintain clear documentation for handover

How You'll Work.

Team & Collaboration

Work with internal users; Work with vendors

Full Job Description

### Role Purpose 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 workf

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