An LLM-Powered Agent for Real-Time Analysis of the Vietnamese IT Job Market
Minh-Thuan Nguyen, Thien Vo-Thanh, Thai-Duy Dinh, Xuan-Quang Phan, Tan-Ha Mai, Lam-Son L\^e

TL;DR
This paper introduces an AI-powered conversational agent that provides real-time, data-driven insights into Vietnam's IT job market by analyzing thousands of job postings using LLMs and tool-augmented reasoning.
Contribution
It presents a novel AI system that automates labor market analysis and offers personalized career guidance through real-time data processing and advanced reasoning capabilities.
Findings
Analyzed 3,745 job postings successfully.
Demonstrated complex multi-step query answering.
Generated real-time visualizations and career advice.
Abstract
Individuals entering Vietnam's dynamic Information Technology (IT) job market face a critical gap in reliable career guidance. Existing market reports are often outdated, while the manual analysis of thousands of job postings is impractical for most. To address this challenge, we present the AI Job Market Consultant, a novel conversational agent that delivers deep, data-driven insights directly from the labor market in real-time. The foundation of our system is a custom-built dataset created via an automated pipeline that crawls job portals using Playwright and leverages the Large Language Model (LLM) to intelligently structure unstructured posting data. The core of our system is a tool-augmented AI agent, based on the ReAct agentic framework, which enables the ability of autonomously reasoning, planning, and executing actions through a specialized toolbox for SQL queries, semantic…
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Taxonomy
TopicsExpert finding and Q&A systems · Personal Information Management and User Behavior · Information Systems Education and Curriculum Development
