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Bulk resume screening & JD matching with GPT-4 for HR teams

Trung TranTrung Tran
2418 views
2/3/2026
Lead GenerationJotFormAutomationSalesforceCRM
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TalentFlow AI – Bulk Resume Screening with JD Matching

Watch the video Automatically extract, evaluate, and shortlist multiple resumes against a selected job description using GPT-4. This smart, scalable n8n workflow helps HR/TA teams streamline hiring decisions while keeping results structured, auditable, and easy to share.

👤 Who’s it for

This workflow is designed for:

  • HR or Talent Acquisition (TA) teams handling multiple candidates per role
  • Recruiters who want AI-assisted resume screening to save time and reduce bias
  • Organizations that want to automatically log evaluations and keep stakeholders updated in real-time via Slack or Sheets

⚙️ How it works / What it does

  1. HR/TA uploads multiple candidate resumes and selects a job role
  2. Each resume is:
    • Uploaded to Google Drive
    • Parsed with GPT-4 to extract structured profile data
  3. The job description for the selected role is:
    • Retrieved from Google Sheets
    • Downloaded from Drive and parsed
  4. The profile + JD are sent to an AI agent to generate:
    • Fit score
    • Strengths & gaps
    • Final recommendation
  5. Results are:
    • Appended to the evaluation tracking sheet
    • Optionally shared with the hiring team on Slack
    • Used to trigger emails to qualified or unqualified candidates

🛠️ How to set up

  1. Clone or import the workflow into your n8n instance
  2. Connect your integrations:
    • Google Sheets (positions & evaluation form)
    • Google Drive (CV & JD folders)
    • OpenAI API (GPT-4)
    • Slack (for notifications)
    • (Optional) SendGrid or SMTP for email notifications
  3. Update Google Sheets structure:
    • Positions sheet: maps Job Role → JD file link
    • Evaluation form: stores evaluation results
  4. Prepare Drive folders:
    • /cv folder for uploaded resumes
    • /jd folder for job description PDFs

📋 Requirements

  • ✅ n8n (hosted or self-hosted)
  • ✅ OpenAI GPT-4 account (used in Profile & JD evaluator agents)
  • ✅ Google Drive + Google Sheets access
  • ✅ Slack workspace + bot token
  • (Optional) SendGrid or email credentials for candidate follow-up

🎨 How to customize the workflow

  • Change the fit score threshold in the Candidate qualified? node
  • Edit Slack message content/formatting to match your company tone
  • Add additional candidate metadata to Sheets or Slack messages
  • Use a webhook trigger to integrate with your ATS or job board
  • Swap GPT-4 with Claude or Gemini if you prefer other AI services
  • Expand to include multi-position batch screening logic

Happy Hiring! 🚀
Automated with love using n8n

n8n Bulk Resume Screening & JD Matching with GPT-4 for HR Teams

This n8n workflow automates the process of bulk resume screening and job description (JD) matching using GPT-4, streamlining the initial stages of recruitment for HR teams.

What it does

This workflow simplifies the process of evaluating multiple resumes against a job description by:

  1. Triggering the workflow: It can be initiated either manually or via a web form submission.
  2. Reading Job Descriptions: It reads a job description from a Google Sheets spreadsheet.
  3. Uploading Resumes: It allows for the upload of multiple resumes (binary files) from Google Drive.
  4. Extracting Resume Content: It extracts text content from the uploaded resume files.
  5. Filtering Resumes: It filters resumes based on criteria (e.g., minimum match score) defined in a "Code" node.
  6. AI-Powered Matching: It uses an OpenAI Chat Model (GPT-4) within a "Basic LLM Chain" and "AI Agent" to perform job description matching against resume content.
  7. Parsing AI Output: It uses a "Structured Output Parser" to extract relevant information from the AI's response (e.g., match score, relevant skills).
  8. Conditional Processing: It uses an "If" node to branch the workflow based on the AI matching results.
  9. Notifying HR: For highly matched candidates, it sends a notification to a Slack channel.
  10. Sending Rejection Emails: For candidates who don't meet the criteria, it sends a rejection email via SendGrid.
  11. Merging Results: It merges the results from different branches to provide a comprehensive overview.
  12. Logging Results: It logs the screening results back into a Google Sheet.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Google Sheets Account: To store job descriptions and log screening results.
  • Google Drive Account: To store and access candidate resumes.
  • OpenAI API Key: For the GPT-4 model used in the AI Agent and LLM Chain.
  • Slack Account: For sending notifications to HR teams.
  • SendGrid Account: For sending automated rejection emails.

Setup/Usage

  1. Import the workflow: Download the JSON file and import it into your n8n instance.
  2. Configure Credentials:
    • Set up credentials for Google Sheets, Google Drive, OpenAI, Slack, and SendGrid in your n8n instance.
  3. Configure Google Sheets (Node 18):
    • Specify the spreadsheet and sheet name where your job descriptions are located.
    • Specify the spreadsheet and sheet name where you want to log the screening results.
  4. Configure Google Drive (Node 58):
    • Specify the folder where candidate resumes are uploaded.
  5. Configure OpenAI Chat Model (Node 1153):
    • Ensure your OpenAI API key is correctly configured.
    • You might need to adjust the model (e.g., gpt-4) and other parameters based on your needs.
  6. Configure AI Agent (Node 1119) and Basic LLM Chain (Node 1123):
    • Review and adjust the prompts and tools used by the AI agent and LLM chain to ensure accurate JD matching.
  7. Configure Structured Output Parser (Node 1179):
    • Define the expected JSON schema for the AI's output (e.g., match_score, relevant_skills, summary).
  8. Configure If Node (Node 20):
    • Adjust the conditions for filtering candidates (e.g., match_score > 0.7).
  9. Configure Slack (Node 40):
    • Specify the Slack channel to which high-match candidate notifications should be sent.
  10. Configure SendGrid (Node 439):
    • Set up the sender email, recipient email (can be dynamically pulled from resume data), and the rejection email template.
  11. Activate the workflow: Once configured, activate the workflow.
  12. Trigger the workflow:
    • Manually: Run the workflow directly from the n8n editor.
    • Via Form Submission (Node 1225): Share the generated form URL and submit data to trigger the workflow. This is ideal for integrating with external forms or applications where new resumes are submitted.
    • Via Google Drive (Node 58): The workflow can be configured to trigger when new files are added to a specific Google Drive folder.

This workflow provides a robust and intelligent solution for automating a significant portion of the resume screening process, allowing HR professionals to focus on more strategic tasks.

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