Job Application Assistant (Agentic AI)

An AI-powered Job Application Assistant built using CrewAI multi-agent architecture that automatically analyzes job postings, researches companies, tailors resumes, and generates personalized cover letters.

This project demonstrates practical implementation of Agentic AI workflows, where multiple specialized AI agents collaborate sequentially to produce high-quality job application materials.

---

Features

Multi-Agent AI Workflow (CrewAI)
Job Posting Analysis
Automated Company Research
Resume Tailoring based on job requirements
Personalized Cover Letter Generation
Sequential Agent Collaboration
Resume PDF parsing tool

---

How It Works

The system uses multiple specialized AI agents that collaborate like a real hiring assistant team:

Job Posting Analyzer

• Extracts required skills
• Identifies key responsibilities
• Detects company culture signals
• Understands hiring priorities

Company Research Specialist

• Searches company information
• Finds mission, values, products
• Retrieves recent company news
• Helps personalize applications

Resume Customization Expert

• Reads resume PDF
• Highlights relevant experience
• Injects job-specific keywords
• Reorders content for impact

Cover Letter Specialist

• Generates personalized cover letters
• Connects candidate experience to role
• Uses company research insights

---

Architecture

User Input
   ↓
Job Posting Analyzer Agent
   ↓
Company Research Agent
   ↓
Resume Tailoring Agent
   ↓
Cover Letter Writer Agent
   ↓
Final Application Output

Agents run sequentially using CrewAI workflow orchestration.

---

Project Structure

Job-Application-Assistant/
│
├── main.py          # Entry point (CLI application)
├── agents.py        # Agent definitions
├── tasks.py         # Task orchestration logic
├── tools.py         # Custom tools (PDF resume reader)
├── requirements.txt
├── resume.pdf       # User resume (input)
└── outputs/         # Generated applications

---

Installation

Clone repository

git clone https://github.com/Samakcha/Job-Application-Assistant.git
cd Job-Application-Assistant

Create virtual environment

python -m venv venv
source venv/bin/activate      # Mac/Linux
venv\Scripts\activate         # Windows

Install dependencies

pip install -r requirements.txt

---

Environment Variables

Create .env file:

OPENAI_API_KEY=your_api_key_here
SERPER_API_KEY=your_serper_key_here

(Optional: Gemini LLM setup can be enabled inside agents.py.)

---

Usage

Place your resume as:

resume.pdf

Run:

python main.py

You will be prompted to:

1. Enter company name
2. Paste job posting text

---

Output

Generated application materials will be saved in:

outputs/<company_name>_application.txt

Includes:

• Job analysis
• Company research summary
• Tailored resume
• Personalized cover letter

---

Technologies Used

• Python
• CrewAI (Agentic workflows)
• LLM Agents
• Serper Search Tool
• PyPDF2
• dotenv

---

Why This Project?

This project showcases:

• Real-world Agentic AI implementation
• Multi-agent collaboration patterns
• Automated workflow orchestration
• Practical AI productivity tooling

Ideal for demonstrating:

• AI engineering skills
• LLM orchestration
• Agent-based system design

---

Future Improvements

• Web UI (Next.js or React)
• Job scraping automation
• LinkedIn integration
• Multiple resume versions
• RAG-based resume memory
• Async agent execution

---

Author

Built by Samakcha Mishra

---

If you like this project

Give it a star and feel free to contribute!