Athena — mahmoud-consultancy/architecture.md

Consultancy Tech Stack - System Architecture Overview

System Components

1. Job Scraper Service (/scraper)

  • Purpose: Automated collection of job vacancies from multiple sources
  • Technology Stack: Python/Node.js, Puppeteer/Playwright, Redis/Queue system
  • Key Features: Multi-source scraping, duplicate detection, data validation
  • Data Storage: PostgreSQL for structured data, S3/File storage for attachments

2. AI Rewriting Funnel (/ai-funnel)

  • Purpose: Intelligent transformation of scraped job descriptions
  • Technology Stack: Python, OpenAI API/Anthropic Claude, FastAPI
  • Key Features: Content rewriting, brand integration, quality assurance
  • ML Pipeline: Training data management, model versioning, A/B testing

3. Vacancy Website & Portal (/website)

  • Purpose: Public job board and employee management system
  • Technology Stack: Astro, React/Vue components, TailwindCSS
  • Key Features: Job listings, time tracking, employee portal, reporting
  • Authentication: Auth0/Supabase Auth, role-based access control

Data Flow Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Job Sources   │───▶│   Job Scraper    │───▶│   Raw Job DB    │
│ (Multiple Sites)│    │   Service        │    │  (PostgreSQL)   │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                                                         │
                                                         ▼
┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│ Published Jobs  │◀───│  AI Rewriting    │◀───│  Processing     │
│   Website       │    │   Funnel         │    │    Queue        │
└─────────────────┘    └──────────────────┘    └─────────────────┘

Technology Decisions

Database Strategy

  • Primary DB: PostgreSQL for transactional data
  • Cache Layer: Redis for session management and job processing queues
  • File Storage: AWS S3 or local storage for resumes and documents
  • Search: Elasticsearch for advanced job search capabilities

API Architecture

  • API Gateway: Kong/Nginx for routing and rate limiting
  • Microservices: Each component as independent service
  • Message Queue: RabbitMQ/Redis for async processing
  • Monitoring: Prometheus + Grafana for system metrics

Frontend Architecture

  • Framework: Astro with React/Vue islands for dynamic components
  • Styling: TailwindCSS for consistent design system
  • State Management: Zustand/Pinia for client-side state
  • Form Handling: React Hook Form/VeeValidate with validation

Deployment Architecture

Development Environment

  • Local Development: Docker Compose for all services
  • Database: Local PostgreSQL container
  • External APIs: Mock services for development

Production Environment

  • Cloud Provider: AWS/Digital Ocean/Vercel
  • Container Orchestration: Docker + ECS/Kubernetes
  • CDN: CloudFront/Cloudflare for static assets
  • Monitoring: CloudWatch/DataDog for logs and metrics

Security Considerations

Data Protection

  • Encryption: TLS 1.3 for data in transit
  • Database: Encrypted at rest
  • Personal Data: GDPR compliance for candidate information
  • API Security: JWT tokens, rate limiting, input validation

Access Control

  • Authentication: Multi-factor authentication for employees
  • Authorization: Role-based permissions (Employee, Manager, Admin)
  • API Keys: Separate keys for internal services
  • Audit Logging: Complete audit trail for all data access

Scalability Considerations

Performance Optimization

  • Caching Strategy: Multi-level caching (CDN, API, Database)
  • Database Optimization: Read replicas, query optimization
  • Background Processing: Async job processing for heavy operations
  • Load Balancing: Auto-scaling based on demand

Growth Planning

  • Horizontal Scaling: Stateless services for easy scaling
  • Database Sharding: Plan for data partitioning if needed
  • CDN Strategy: Global content distribution
  • Monitoring: Proactive alerting for performance issues

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