JobBoard - Full-Stack Job Platform
Description
JobBoard is a comprehensive full-stack job platform built with Python/Flask backend and Next.js frontend, featuring dual user authentication for companies and job seekers. The platform includes advanced A/B testing capabilities using LLM-enhanced job descriptions, comprehensive API endpoints for job management, and automated CI/CD pipeline with Docker containerization. The system implements sophisticated analytics and conversion tracking to optimize job posting effectiveness.
Challenges & Solutions
Key challenges included implementing a robust dual authentication system for different user types, creating an efficient A/B testing framework for job descriptions using Together.ai LLM integration, and developing a comprehensive API with proper authorization and data validation. The project required complex database design to handle job applications, user management, and analytics tracking while maintaining performance and scalability.
Technical Achievements
- Dual Authentication System: Implemented separate authentication flows for companies and job seekers with role-based access control
- A/B Testing Framework: Built comprehensive A/B testing system comparing original vs LLM-enhanced job descriptions with conversion tracking
- RESTful API Design: Created 20+ API endpoints with proper HTTP methods, status codes, and comprehensive error handling
- LLM Integration: Integrated Together.ai for automated job description enhancement and optimization
- Analytics Dashboard: Developed conversion tracking and visualization system with charts and statistical analysis
- Docker Containerization: Implemented containerized deployment with proper environment configuration and dependency management
- CI/CD Pipeline: Established automated testing, building, and deployment workflow using GitHub Actions
- Database Design: Created optimized MongoDB schemas for companies, job seekers, job posts, and applications with proper indexing