An LLM-Powered Agent for Real-Time Analysis of the Vietnamese IT Job Market
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866917090080849920 |
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| author | Nguyen, Minh-Thuan Vo-Thanh, Thien Dinh, Thai-Duy Phan, Xuan-Quang Mai, Tan-Ha Lê, Lam-Son |
| author_facet | Nguyen, Minh-Thuan Vo-Thanh, Thien Dinh, Thai-Duy Phan, Xuan-Quang Mai, Tan-Ha Lê, Lam-Son |
| contents | 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 Existing market reports are often outdated, while the manual analysis of thousands of job postings is impractical for most.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 search, and data visualization. Our prototype successfully collected and analyzed 3,745 job postings, demonstrating its ability to answer complex, multi-step queries, generate on-demand visualizations, and provide personalized career advice grounded in real-world data. This work introduces a new paradigm for labor market analysis, showcasing how specialized agentic AI systems can democratize access to timely, trustworthy career intelligence for the next generation of professionals. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_14767 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An LLM-Powered Agent for Real-Time Analysis of the Vietnamese IT Job Market Nguyen, Minh-Thuan Vo-Thanh, Thien Dinh, Thai-Duy Phan, Xuan-Quang Mai, Tan-Ha Lê, Lam-Son Information Retrieval Artificial Intelligence Computers and Society 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 search, and data visualization. Our prototype successfully collected and analyzed 3,745 job postings, demonstrating its ability to answer complex, multi-step queries, generate on-demand visualizations, and provide personalized career advice grounded in real-world data. This work introduces a new paradigm for labor market analysis, showcasing how specialized agentic AI systems can democratize access to timely, trustworthy career intelligence for the next generation of professionals. |
| title | An LLM-Powered Agent for Real-Time Analysis of the Vietnamese IT Job Market |
| topic | Information Retrieval Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2511.14767 |