7.4 KiB
7.4 KiB
KAAUH Applicant Tracking System (ATS) - High Level Design Document
1. Executive Summary
This document outlines the High-Level Design (HLD) for the King Abdulaziz University Hospital (KAAUH) Applicant Tracking System (ATS). The system is designed to streamline the recruitment process by providing comprehensive tools for job posting, candidate management, interview scheduling, and integration with external platforms.
2. System Overview
2.1 Vision
To create a modern, efficient, and user-friendly recruitment management system that automates and optimizes the hiring process at KAAUH.
2.2 Mission
The ATS aims to:
- Centralize recruitment activities
- Improve candidate experience
- Enhance recruiter efficiency
- Provide data-driven insights
- Integrate with external platforms (Zoom, LinkedIn, ERP)
2.3 Goals
- Reduce time-to-hire
- Improve candidate quality
- Enhance reporting and analytics
- Provide seamless user experience
- Ensure system scalability and maintainability
3. Architecture Overview
3.1 Technology Stack
- Backend: Django 5.2.1 (Python)
- Frontend: HTML5, CSS3, JavaScript, Bootstrap 5
- Database: SQLite (development), PostgreSQL (production)
- APIs: REST API with Django REST Framework
- Real-time: HTMX for dynamic UI updates
- Authentication: Django Allauth with OAuth (LinkedIn)
- File Storage: Local filesystem
- Task Queue: Celery with Redis
- Communication: Email, Webhooks (Zoom)
3.2 System Architecture
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Web Browser │ │ Mobile App │ │ Admin Panel │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│ │ │
└───────────────────────┼───────────────────────┘
│
┌─────────────────┐
│ Load Balancer │
└─────────────────┘
│
┌─────────────────┐
│ Web Server │
│ (Gunicorn) │
└─────────────────┘
│
┌─────────────────┐
│ Application │
│ (Django) │
└─────────────────┘
│ │
┌───────────────┴─────────┐ ┌─────┴────────────────┐
│ Database Layer │ │ External Services│
│ (SQLite/PostgreSQL) │ │ (Zoom, LinkedIn) │
└─────────────────────────┘ └─────────────────────┘
4. Core Components
4.1 User Management
- Role-based Access Control:
- System Administrators
- Hiring Managers
- Recruiters
- Interviewers
- Candidates
- Authentication:
- User registration and login
- LinkedIn OAuth integration
- Session management
4.2 Job Management
- Job Posting:
- Create, edit, delete job postings
- Job templates and cloning
- Multi-language support
- Approval workflows
- Job Distribution:
- LinkedIn integration
- Career page management
- Application tracking
4.3 Candidate Management
- Candidate Database:
- Profile management
- Resume parsing and storage
- Skills assessment
- Candidate scoring
- Candidate Tracking:
- Application status tracking
- Stage transitions
- Communication logging
- Candidate relationship management
4.4 Interview Management
- Scheduling:
- Automated interview scheduling
- Calendar integration
- Time slot management
- Buffer time configuration
- Video Interviews:
- Zoom API integration
- Meeting creation and management
- Recording and playback
- Interview feedback collection
4.5 Form Builder
- Dynamic Forms:
- Multi-stage form creation
- Custom field types
- Validation rules
- File upload support
- Application Processing:
- Form submission handling
- Data extraction and storage
- Notification systems
4.6 Reporting and Analytics
- Dashboards:
- Executive dashboard
- Recruitment metrics
- Candidate analytics
- Department-specific reports
- Data Export:
- CSV, Excel, PDF exports
- Custom report generation
- Scheduled reports
5. Integration Architecture
5.1 External API Integrations
- Zoom Video Conferencing:
- Meeting creation and management
- Webhook event handling
- Recording and transcription
- LinkedIn Recruitment:
- Job posting automation
- Profile synchronization
- Analytics tracking
- ERP Systems:
- Employee data synchronization
- Position management
- Financial integration
5.2 Internal Integrations
- Email System:
- Automated notifications
- Interview reminders
- Status updates
- Calendar System:
- Interview scheduling
- Availability management
- Conflict detection
6. Security Architecture
6.1 Authentication & Authorization
- Multi-factor authentication support
- Role-based access control
- JWT token authentication
- OAuth 2.0 integration
6.2 Data Protection
- Data encryption at rest and in transit
- Secure file storage
- Personal data protection
- Audit logging
6.3 System Security
- Input validation and sanitization
- SQL injection prevention
- XSS protection
- CSRF protection
- Rate limiting
7. Scalability & Performance
7.1 Performance Optimization
- Database indexing
- Query optimization
- Caching strategies (Redis)
- Asynchronous task processing (Celery)
7.2 Scalability Considerations
- Horizontal scaling support
- Load balancing
- Database replication
- Microservices-ready architecture
8. Deployment & Operations
8.1 Deployment Strategy
- Container-based deployment (Docker)
- Environment management
- CI/CD pipeline
- Automated testing
8.2 Monitoring & Maintenance
- Application monitoring
- Performance metrics
- Error tracking
- Automated backups
9. Future Roadmap
9.1 Phase 1 (Current)
- Core ATS functionality
- Basic reporting
- Zoom and LinkedIn integration
- Mobile-responsive design
9.2 Phase 2 (Next 6 months)
- Advanced analytics
- AI-powered candidate matching
- Enhanced reporting
- Mobile app development
9.3 Phase 3 (Next 12 months)
- Voice interview support
- Video interview AI analysis
- Advanced integrations
- Multi-tenant support
10. Conclusion
The KAAUH ATS system is designed to be a comprehensive, modern, and scalable solution for managing the recruitment lifecycle. By leveraging Django's robust framework and integrating with external platforms, the system will significantly improve recruitment efficiency and provide valuable insights for decision-making.
Document Version: 1.0 Last Updated: October 17, 2025