AI Resume Generation – Integrated OpenAI (GPT-OSS-120b) to generate, rephrase, and tailor resume sections based on job descriptions.
ATS Optimization & Scoring – Extracts keywords, calculates match scores, highlights missing skills, and provides AI-driven recommendations.
Authentication with OAuth2 + JWT –
Implemented Passport.js (Google Strategy) for OAuth2 login
Combined with JWT to refresh & access tokens for secure sessions
Access token → Expires in 3 hours
Refresh token → Stored securely in cookies (3 days)
Axios interceptors handle auto-renewal & retry failed requests seamlessly
Login & Signup Flows –
Built with RTK Query + custom hooks to manage auth, resume data, and user sessions consistently.
Dependency Injection, OOP & Design Patterns –
Structured the backend with Dependency Injection and Object-Oriented Programming to ensure scalability, modularity, and maintainability.
Resume Parsing –
Used Mammoth and pdf-parse to extract and structure text from DOCX/PDF resumes.
PDF Export –
Leveraged Puppeteer with headless Chromium to convert dynamic HTML/CSS resume templates directly into parsable, ATS-friendly PDFs (not just images).
File Uploads & Storage –
Implemented with Multer + Cloudinary API for secure and scalable file handling.
Global State & Server Data Management –
Redux Toolkit for global state management
TanStack Query for caching, server-state sync, and background updates for fetching & mutating data.
Form Validation –
Enforced robust validation on signup with Zod.
Frontend Performance –
Optimized with lazy loading, memoization, and custom hooks.
Modern UI & Animations & Responsive Design –
Built with Tailwind CSS + Shadcn and smooth Framer Motion animations.
Secure Password Hashing – Used bcrypt to hash user credentials, ensuring robust backend security and safe authentication then stored in DB.
This project brought together AI, secure authentication flows, caching, parsing, and scalable architecture — all in one product that helps job seekers optimize their resumes.