👥 Generate tailored interview questions with GPT-4 based on CV, JD, and round

⚡ 1,292 views · 👥 HR & Recruitment

Description

🤖 Smart Interview Assistant: Tailored Questions Based on CV, JD, and Round

Watch the demo video below:

📌 Who’s it for

This workflow is designed for:

• Recruiters and Talent Acquisition Specialists who want to automate candidate interview prep.
• Hiring Managers conducting multiple interviews and needing personalized question sets.
• Technical Interviewers who want to save time and be well-prepared with relevant questions.

⚙️ How it works / What it does

The Smart Interview Assistant automates the interview preparation process in a few clicks:

1. Accepts:
   • Multiple resumes (PDFs)
   • Selected job role
   • Chosen interview round
2. Extracts structured data from:
   • The candidate’s CV
   • The corresponding Job Description (JD)
3. Uses GPT-4 to analyze:
   • Candidate profile
   • Role requirements
   • Interview round context
4. Generates:
   • Tailored interview questions
   • Expected answers
   • A summarized interview prep report
5. Sends the report directly to the hiring team via email (SMTP)

📁 Google Drive Structure

📂 Root Folder
├── 📁 jd/                          # Stores all job descriptions in PDF format
│   ├── Backend_Engineer.pdf
│   ├── Azure_DevOps_Lead.pdf
│   └── ...
└── 📄 Positions (Google Sheet)    # Maps Job Role ↔ JD File Link

📝 Sample Mapping Sheet:
Positions Sheet

Columns:

• Job Role
• Job Description File URL (pointing to PDF in jd/ folder)

🛠️ How to Set Up

Step 1: Configure API Integrations

• ✅ Connect your OpenAI GPT-4 API Key
• ✅ Enable Google Cloud APIs:
  • Google Sheets API (to read job roles)
  • Google Drive API (to access CV and JD files)
• ✅ Set up SMTP credentials (for email delivery)

Step 2: Prepare Google Drive & Mapping Sheet

1. Create a root folder on Google Drive
2. Inside the root folder:
   • Create a folder named /jd/ and upload all job descriptions (PDFs)
3. Create a Google Sheet named Positions with the following format:

| Job Role                     | Job Description File URL                   |
|-----------------------------|--------------------------------------------|
| Azure DevOps Engineer        | https://drive.google.com/xxx/jd1.pdf       |
| Full-Stack Developer (.NET)  | https://drive.google.com/xxx/jd2.pdf       |

Step 3: Build the Application Form

Use any form tool (e.g., Typeform, Tally, or custom HTML) that collects:

• 📎 Resume file (PDF)
• 🧾 Job Role (dropdown)
• 🔄 Interview Round (dropdown)

Step 4: Resume & JD Extraction

• 🔍 Use Extract from PDF to parse the resume content
• 📄 Retrieve the JD link from the Positions sheet based on the selected Job Role
• 🔗 Use Download file to pull the PDF for processing

Step 5: Analyze with GPT-4

• Run both Resume and JD through a Profile Analyzer Agent (GPT-4 with JSON output)
• Merge results
• Add manual input or mapping for the Interview Round metadata

Step 6: Generate Interview Report

• Use a second GPT-4 agent (e.g., HR Expert Agent) to:
  • Generate 6–8 tailored interview questions
  • Include expected answers and rationale

Step 7: Deliver Final Report

• Format the content as:
  • 📄 PDF (optional)
  • 📨 Email body
• Send the report to the recruiter, hiring manager, or interviewer via SMTP

✅ Requirements

• 🔑 OpenAI GPT-4 API Key
• 📁 Google Drive (for resume and JD storage)
• 📊 Google Sheet (job role mapping)
• 📬 SMTP credentials (host, username, password)
• 🧰 n8n self-hosted or cloud instance with:
  • PDF Parser
  • Google Sheets node
  • HTTP Download node
  • Email node

✏️ How to Customize the Workflow

🔗 Nodes Used

Send Email, Google Sheets, Google Drive, AI Agent, Basic LLM Chain, OpenAI Chat Model

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup