This n8n workflow automates the extraction of detailed job descriptions and salary information from online job postings using Bright Data MCP, OpenAI language models, and various data processing nodes. The process is triggered manually for testing and can be integrated into broader HR or recruitment systems.
The workflow begins with a manual trigger, allowing users to initiate the process on demand. It then sets input fields including the job search URL, job role, and webhook notification URL. The Bright Data MCP Client retrieves the webpage content from the provided URL, which contains the job data.
The raw job description content is processed through an OpenAI language model to extract structured job description details in markdown format, converting it into textual data. Simultaneously, a separate search engine query (Google) is used to gather salary-related data for the specified job role. This data is also analyzed by an OpenAI language model to extract detailed salary information, such as salary range, currency, location, employment type, and benefits.
Extracted salary data and job description are merged and then stored both in a Google Sheet for easy review and as a JSON file saved locally. Additionally, a webhook notification sends the processed job info to an external endpoint, potentially for alerting or further integration.
This workflow is particularly useful for HR teams, recruiters, or market analysts who want real-time, structured insights from online job postings without manual data collection, enabling better market analysis, salary benchmarking, and job description automation.
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