👥 Match LinkedIn jobs and generate cover letters with OpenAI, Apify and Sheets

⚡ 170 views · 👥 HR & Recruitment

💡 Pro Tip — If you’re pulling LinkedIn data through HTTP requests or dealing with API restrictions, there’s a community node called ScraperNode that handles this natively. It has dedicated scrapers for profiles, companies, jobs, and people search — you just pass a URL and get structured data back.

Description

This n8n workflow automatically searches LinkedIn jobs using Apify, compares each job with your resume using AI, calculates a match score, generates a personalized cover letter, and stores everything inside Google Sheets.

High-scoring jobs are instantly sent to Telegram so you can apply faster to the most relevant opportunities.

Workflow Structure

Step 1 — Schedule Trigger

Node: Schedule Trigger

This node automatically starts the workflow every day at a specific time.

What it does

• Runs the workflow automatically
• Eliminates manual execution
• Creates a fully automated job-hunting system

Current Configuration

• Runs daily at 5 PM

Step 2 — Download Resume PDF

Node: Download file

This node downloads the resume PDF from Google Drive.

What it does

• Connects to Google Drive
• Downloads the selected resume file
• Sends the file to the next processing step

Why it matters

Your resume becomes dynamic input for the AI matching system.

Step 3 — Extract Resume Text

Node: Extract from File

This node extracts readable text from the PDF resume.

What it does

• Reads the PDF file
• Extracts plain text content
• Makes the resume understandable for AI

Output

• Resume text
• PDF metadata
• Structured readable content

Step 4 — Read Job Search Filters

Node: Get row(s) in sheet

This node reads job search preferences from Google Sheets.

What it reads

• Job keyword
• Preferred location
• Easy Apply option

Example

Step 5 — LinkedIn Job Scraper

Node: Run an Actor and get dataset

This node uses Apify to scrape LinkedIn job listings.

What it does

• Searches LinkedIn jobs
• Uses keyword + location filters
• Fetches latest job postings
• Supports Easy Apply filtering

Example Search

• Software Developer
• Bangalore
• Easy Apply enabled

Output Includes

• Job title
• Company name
• Job description
• LinkedIn apply link
• Applicant count
• Workplace type

Step 6 — Process Jobs One-by-One

Node: Loop Over Items

This node processes each scraped job individually.

What it does

• Loops through all job listings
• Processes one job at a time
• Prevents AI overload
• Maintains stable execution

Step 7 — AI Resume Matcher

Node: Job Matcher

This is the core AI engine of the workflow.

AI Model Used

• GPT-4.1 Mini

What it does

• Reads your resume
• Reads the job description
• Compares both intelligently
• Calculates a job match score
• Generates a personalized cover letter

AI Output

{
  "score": 80,
  "coverLetter": "Generated personalized cover letter"
}

Step 8 — Parse AI Output

Node: Edit Fields

This node formats the AI response into reusable structured data.

What it does

• Converts raw AI response into JSON
• Cleans output formatting
• Makes fields reusable in later nodes

Output Fields

• Match score
• Cover letter

Step 9 — Save Results to Google Sheets

Node: Append or update row in sheet

This node stores processed jobs inside Google Sheets.

What gets saved

• Job title
• Company
• Location
• Job description
• Apply link
• Match score
• AI-generated cover letter

Step 10 — High Match Score Filter

Node: Score Filter

This node filters only high-quality job matches.

Current Logic

Continue only if:

Score ≥ 50

Step 11 — Telegram Job Alerts

Node: Send a text message

This node sends instant Telegram notifications for top job matches.

What it sends

• Job title
• Company
• Location
• Match score
• Apply link

🔗 Nodes Used

Google Sheets, Telegram, Google Drive, Schedule Trigger, AI Agent, OpenAI Chat Model

📥 Import

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

📖 Importing guide · 🔑 Credential setup