Generate Tailored Interview Questions with GPT-4 Based on CV, JD, and Round

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:

Accepts:
Multiple resumes (PDFs)
Selected job role
Chosen interview round
Extracts structured data from:
The candidate’s CV
The corresponding Job Description (JD)
Uses GPT-4 to analyze:
Candidate profile
Role requirements
Interview round context
Generates:
Tailored interview questions
Expected answers
A summarized interview prep report
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

Create a root folder on Google Drive
Inside the root folder:
Create a folder named /jd/ and upload all job descriptions (PDFs)
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

| Part | Customization Options |
|----------------------------|-------------------------------------------------------------|
| Form UI | Modify the design, dropdown options, or input validations |
| Job Description Source | Replace Google Sheet with Notion, Airtable, or database |
| Interview Metadata | Add job level, region, or language preference |
| AI Prompt Tuning | Adjust prompt phrasing or temperature in GPT nodes |
| Report Format | Generate PDF instead of email body using PDF node |
| Delivery Method | Add internal HR portal webhook or generate downloadable link |