AI Recruitment Platform (ATS)

Project Description

A modern ATS platform designed to parse PDF CVs using multimodal AI, rank candidates against job vacancies using semantic vector search, and orchestrate automated recruitment stages via an external n8n hub.

Core User Stories

• Recruiter - CV Upload: As a recruiter, I want to upload CVs in PDF format so they can be evaluated automatically.
• Recruiter - Vacancy Ranking: As a recruiter, I want a ranking of candidates per job vacancy.
• Recruiter - Seniority Detection: As a recruiter, I want the system to detect seniority to adjust interviews.
• Recruiter - Profile Summary: As a recruiter, I want a concise AI summary of the profile for quick review.
• Hiring Manager - Comparative Scoring: As a hiring manager, I want a comparative score between candidates.
• Recruiter - Stage Automation: As a recruiter, I want candidates to move through recruitment stages automatically.
• Candidate - Automated Emails: As a candidate, I want to receive automated email confirmations for every stage change.
• Talent Team - Vacancy Metrics: As a talent team, we want metrics on the progress per vacancy.

Setup & Prerequisites

1. Google AI Studio Account (Mandatory)

Vector embeddings matching and search operations require a direct call to the Google Gemini Embeddings API (models/gemini-embedding-001).

• Prerequisite: You must obtain a free-tier or paid-tier Gemini API key from Google AI Studio.
• Usage: The embedding model is free for up to 1,500 requests per day (15 requests per minute), which covers standard development and testing requirements.
• Configuration: Add your key to the .env file at the root of the project:

  GEMINI_API_KEY=your_google_ai_studio_api_key_here