AI-Powered Job Search Automator
Budget: ₹1,250 – ₹2,500 INR
Project Description (General / Pitch Deck)
AI-Powered Job Agent: Developed an intelligent SaaS platform that automates the entire job search lifecycle—from discovery to application and follow-up—saving job seekers hours of manual effort.
Smart Aggregation & Filtering: Integrates with major platforms like LinkedIn, Indeed, and Wellfound to scrape and filter real-time job listings based on role, salary, and remote preferences.
Hyper-Personalized Applications: Utilizes LLMs to dynamically rewrite resumes for ATS optimization and generate human-like, role-specific cover letters for every single job application.
Automated Workflow Engine: Features an "Auto-Apply" system that fills forms and uploads documents automatically, coupled with a Kanban-style dashboard to track application statuses.
Intelligent Follow-Up: Includes an automated email system that sends polite, timed follow-ups to recruiters to increase interview conversion rates.
Technical Description (For Developer Resume)
Scalable Backend Architecture: Built using FastAPI and PostgreSQL, employing Redis + Celery to handle asynchronous tasks like web scraping and AI processing efficiently.
Advanced Automation: Implemented Selenium and Playwright scripts to automate login, form-filling, and submission processes across multiple job portals while handling rate limiting.
Generative AI Integration: Integrated LLMs to analyze job descriptions (JD) and perform real-time keyword matching, resume scoring, and content generation.
Modern UI/UX: Designed a responsive, dark-mode dashboard (React/Next.js recommended based on design) with smooth transitions, drag-and-drop Kanban boards, and interactive analytics widgets.
Security & Auth: Secured user data with JWT & OAuth authentication and encrypted storage for credentials and personal documents.
AI-Powered Job Agent: Developed an intelligent SaaS platform that automates the entire job search lifecycle—from discovery to application and follow-up—saving job seekers hours of manual effort.
Smart Aggregation & Filtering: Integrates with major platforms like LinkedIn, Indeed, and Wellfound to scrape and filter real-time job listings based on role, salary, and remote preferences.
Hyper-Personalized Applications: Utilizes LLMs to dynamically rewrite resumes for ATS optimization and generate human-like, role-specific cover letters for every single job application.
Automated Workflow Engine: Features an "Auto-Apply" system that fills forms and uploads documents automatically, coupled with a Kanban-style dashboard to track application statuses.
Intelligent Follow-Up: Includes an automated email system that sends polite, timed follow-ups to recruiters to increase interview conversion rates.
Technical Description (For Developer Resume)
Scalable Backend Architecture: Built using FastAPI and PostgreSQL, employing Redis + Celery to handle asynchronous tasks like web scraping and AI processing efficiently.
Advanced Automation: Implemented Selenium and Playwright scripts to automate login, form-filling, and submission processes across multiple job portals while handling rate limiting.
Generative AI Integration: Integrated LLMs to analyze job descriptions (JD) and perform real-time keyword matching, resume scoring, and content generation.
Modern UI/UX: Designed a responsive, dark-mode dashboard (React/Next.js recommended based on design) with smooth transitions, drag-and-drop Kanban boards, and interactive analytics widgets.
Security & Auth: Secured user data with JWT & OAuth authentication and encrypted storage for credentials and personal documents.