Block 1 - When clicking ‘Execute workflow’
- Type / Role
- n8n-nodes-base.manualTrigger - manualTrigger
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
What Problem Does it Solve This workflow automates the process of finding and collecting job postings from LinkedIn, eliminating the need for manual job searching. It’s designed to save time and en...
n8n-nodes-base.manualtrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatgooglegemini, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.splitinbatches, n8n-nodes-base.html, n8n-nodes-base.code, n8n-nodes-base.stickynote
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Abdullah Alshiekh.
Original n8n.io sourceThis workflow automates the process of finding and collecting job postings from LinkedIn, eliminating the need for manual job searching. It’s designed to save time and ensure you don’t miss out on new opportunities by automatically populating a spreadsheet with key job details.
Automated Data Collection: The workflow pulls job posts from a LinkedIn search via an RSS feed.
Intelligent Data Extraction: It scrapes the full job description and uses AI to summarize the key benefits and job responsibilities into a concise format.
Centralized Database: All collected and processed information is automatically saved to a Google Sheet, providing a single source of truth for your job search.
The workflow starts when manually triggered. It reads the job posts from a given RSS feed, processing each one individually. For each job, it fetches the full webpage content to extract structured data. This data is then cleaned and passed to an AI model, which generates a brief summary of the job and its benefits. Finally, a new row is either added or updated in a Google Sheet with all the collected details, including the job title, company name, and AI-generated summary.
This workflow is highly customizable to fit your specific needs.
RSS Feed: To get started, you'll need to provide the RSS feed URL for your desired LinkedIn job search. We can help you set this up.
AI Model: The workflow uses Google Gemini by default, but it can be adjusted to work with other AI platforms.
Data Destination: The output is configured to a Google Sheet, but it can easily be changed to a different platform like Notion or a CRM.
AI Prompting: The AI's instructions are customizable, so you can tailor the output to extract different information or match a specific tone.
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This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
| Workflow | Scrape LinkedIn jobs with Gemini AI and store in Google Sheets using RSS |
|---|---|
| Complexity | advanced |
| Nodes | 17 |
| Categories | AI Summarization |
| Author | Abdullah Alshiekh |
| Published | 03 Sept 2025 |
Use the JSON export at /data/workflows/8219/8219.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
What Problem Does it Solve This workflow automates the process of finding and collecting job postings from LinkedIn, eliminating the need for manual job searching. It’s designed to save time and en...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your AI Summarization use case.