🤖 AI Job Application Assistant | Gen AI Capstone 2025

This project was built as part of the Google Gen AI Intensive Capstone 2025. It showcases how Generative AI can automate the job application process using Google Gemini Pro.

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🔍 Overview

The AI Job Application Assistant helps job seekers streamline their application process by:

• Matching resumes with job descriptions
• Scoring job-resume compatibility
• Suggesting customized resume bullet points
• Auto-generating a personalized cover letter
• Outputting all data in structured JSON format

All of this is done using Generative AI prompts and automation, reducing manual effort while improving quality and personalization.

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✨ Key Features

• ✅ Match score calculation between job descriptions and resumes
• ✅ AI-generated resume enhancements
• ✅ Tailored cover letter creation
• ✅ JSON output for use in trackers or dashboards
• ✅ Lightweight agent-like logic for step-by-step automation

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🧠 GenAI Techniques Used

• Retrieval-Augmented Generation (RAG-style prompts)
• Structured Output (JSON formatting)
• Agent-style Task Automation
• Few-shot Prompt Engineering
• Grounding
• LOng Context Handling

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🛠 Built With

• Google Gemini Pro (via google-generativeai SDK)
• Python (Jupyter Notebook / Kaggle)
• Markdown, JSON

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🚀 Setup & Usage

1. Install dependencies

pip install google-generativeai

2. Set your Google API key

import google.generativeai as genai genai.configure(api_key="your_google_api_key_here")

3. Run the notebook

Follow the code steps to input your resume and a job description. The model will generate match insights, JSON data, and a custom cover letter.

📁 Project Structure

AI-Job-Application-Assistant/ ├── README.md

├── Capstone_Notebook.ipynb

├── assets/

│ └── thumbnail.png

└── examples/

└── sample_outputs.json

📹 Demo & Blog

📖 Blog Post: Read on Medium

🎥 Video Demo:Watch on YouTube

📓 Kaggle Notebook:View on Kaggle

📈 Future Enhancements

LinkedIn/Indeed job scraping

Google Sheets integration for tracking

Gmail API for auto-sending applications

Streamlit-based UI for broader use

🙌 Acknowledgments

Thanks to the Google Gen AI Intensive Team, Kaggle, and the amazing GenAI community!

📜 License

This project is licensed under the MIT License.

Note: You're free to use, share, and adapt this project with proper credit. Please do not rebrand, resell, or redistribute modified versions without clear attribution to the original author.

© 2025 Sreeja Bethu. All rights reserved.