JobPilot Ecosystem
A next-generation career and recruitment platform that bridges the gap between job seekers, employers, and trainers. Powered by advanced Google Gemini AI, JobPilot automates CV screening, intelligently recommends career-accelerating courses, and provides a 24/7 intelligent recruiting assistant.
JOBPILOT
Final Project Overview & Technical Architecture
JobPilot completely revolutionizes the standard job board model by deeply integrating Generative AI into every aspect of the recruitment funnel. Designed with a robust multi-role architecture (Admin, Employer, Trainer, Job Seeker), the platform ensures a tailored, seamless dashboard experience for every user type.
The frontend is built on the bleeding-edge Angular 19 framework combined with Tailwind CSS v4, resulting in highly reactive, glassmorphic interfaces. The backend leverages Node.js and Express to orchestrate a complex MySQL relational database while acting as a secure middleware layer for Google's Gemini AI API.
AI Data Handling
System securely transmits parsed CV JSON payloads to Gemini via structured API requests, instructing the LLM to rate applicant qualifications against specific job constraints in real-time.
Role-Based Ecosystem
A tightly coupled JWT authentication flow instantly resolves permissions across 4 distinct dashboard hierarchies, protecting routes and API endpoints simultaneously.
Core AI Features & Achievements
Smart CV Parser & Matcher
When employers view applicants, the backend dynamically requests the AI to evaluate each CV against the specific Job requirements, generating a 0-100% "Match Score" to eliminate manual screening fatigue.
Context-Aware AI Chatbot
Integrated a 24/7 intelligent assistant capable of understanding the context of the exact job posting a user is viewing, allowing applicants to ask highly specific questions about requirements and culture.
Predictive Course Enhancements
The AI identifies skill gaps in a candidate's profile and cross-references them against courses published by Trainers, autonomously suggesting personalized learning paths to improve their employability.
Project Details
- Completion Date Sept 2026
- Category AI / Full Stack Web App
- Type Final Project Report
- Role Full Stack Architect