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

🤖 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 |