JobWise

A next-generation, automated hiring platform connecting employers with top-tier candidates.

View Live Platform

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Overview

JobWise originated as a purely Python-based backend API, created to explore advanced backend architecture and data processing. Realizing the core logic was robust and highly scalable, I decided to take the project Full-Stack. Utilizing AI and modern UI principles to accelerate the design workflow, I conceptualized and built a stunning React frontend architecture to bring the Python engine to life.

What started as a learning exercise is now a fully functional, sleek SaaS hiring platform.

Key Features

Candidate Experience

• Intelligent Onboarding: Candidates can upload their resumes (PDF format), and the system automatically extracts and categorizes their skills using PyPDF2.
• Smart Match Dashboard: Candidates instantly view active jobs sorted by a dynamic Match Score algorithm that compares their parsed skills against the employer's requirements.
• Frictionless Application: Premium UI interactions allow candidates to apply for jobs seamlessly with real-time status tracking.

Employer Experience

• Job Management: Employers can create, edit, and manage job listings with custom salary ranges, locations, and structured skill arrays.
• Applicant Tracking System (ATS): Employers receive beautifully formatted applicant cards featuring match scores and dynamic statuses (Applied, Reviewing, Accepted, Rejected), alongside quick-action controls.

Technical & UI Architecture

• Unified Design System: A strictly enforced CSS architecture utilizing CSS Variables (index.css) ensures flawless cross-component consistency.
• Premium Interactions: Physics-based CSS hover transitions simulate a high-end "Framer Motion" style premium feel.
• Secure Authentication: JWT-based authentication using bcrypt hashing. Accounts are strictly validated and secured via Email login protocols.

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Tech Stack

Frontend Architecture:

• React (Vite)
• React Router DOM
• Phosphor Icons
• Vanilla CSS (Custom CSS Variables Design System)

Backend Architecture:

• FastAPI (Python)
• SQLAlchemy (ORM) & Alembic (Migrations)
• PostgreSQL
• PyPDF2 (Resume parsing)
• Passlib & python-jose (JWT Auth)

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Local Development Setup

1. Backend Environment

1. Open a terminal in the root directory and create a virtual environment:

   python -m venv .venv
   .\.venv\Scripts\Activate.ps1  # Windows
   # source .venv/bin/activate    # Mac/Linux

2. Install backend dependencies:

   pip install -r requirements.txt

3. Setup your PostgreSQL Database & Environment Variables:

   • Copy .env.example to .env.
   • Update the DATABASE_URL to point to your local PostgreSQL instance.

4. Run database migrations to build the schema:

   alembic upgrade head

5. Start the FastAPI server:

   uvicorn app.main:app --reload

   (The backend runs on http://localhost:8000. Swagger API documentation is automatically generated at http://localhost:8000/docs)

2. Frontend Environment

1. Open a new terminal and navigate to the frontend directory:

   cd frontend

2. Install Node dependencies:

   npm install

3. Start the Vite React development server:

   npm run dev

   (The frontend runs on http://localhost:5173)

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