LLD
AI-Powered Recruitment Automation System
Low-Level Design Document (LLD)
馃摌 Table of Contents
- System Overview
- Module Breakdown
- API Design
- Database Design
- Business Workflow
- AI Integration Points
- System Architecture
1. System Overview
1.1 馃幆 Purpose
Automate the recruitment pipeline from resume ingestion to candidate ranking using NLP-based parsing, vector embeddings, and AI-powered re-ranking.
1.2 鈿欙笍 Key Capabilities
- Incremental Resume Ingestion: Fetch new resumes from Gmail on schedule
- Automated Resume Parsing: Extract structured data (skills, experience, education, contact)
- Semantic Matching: Use embeddings to find similar candidates to job descriptions
- AI Re-Ranking: Re-rank top candidates using GPT-4o-mini for better precision
- Dashboard: HR views ranked candidates with explainability
1.3 馃О Technology Stack
| Layer | Technology |
|---|---|
| Frontend | React.js + Tailwind CSS |
| Backend | Node.js + Express.js |
| Database | PostgreSQL 15+ with pgvector extension |
| AI/ML | OpenAI GPT-4o-mini |
| Embeddings | OpenAI text-embedding-3-small |
| Email Integration | Gmail API with OAuth 2.0 |
| Scheduler | node-cron |
馃 Additional Components
| Component | Technology |
|---|---|
| AI/ML | OpenAI GPT-4o-mini |
| Vector Embeddings | OpenAI text-embedding-3-small |
| Email Integration | Gmail API with OAuth 2.0 |
| Scheduler | node-cron |