AI-Powered Resume Screening System

Recruiters and hiring teams often spend hours manually reviewing resumes before they even reach the interview stage. As application volume grows, this process becomes slower, more expensive, and increases the risk of overlooking qualified candidates.

I built an AI-powered resume screening system that automates the entire workflow — from receiving resumes to delivering ranked candidate recommendations.

Monitors incoming job applications automatically

Extracts and analyzes resume content using AI

Compares each candidate against the job requirements using semantic search

Ranks applicants based on relevance and suitability

Stores candidate data for future searches and analysis

Sends the screening results directly to the hiring team's inbox

n8n — workflow orchestration

Google Gemini — AI content analysis

OpenRouter LLMs — language model routing

Qdrant Vector Database — semantic search and candidate matching

PostgreSQL — candidate data storage

Gmail API — automated result delivery

The goal wasn't just to automate resume screening — it was to help hiring teams make faster, more consistent, and more informed hiring decisions while reducing repetitive manual work.

Automation should eliminate repetitive tasks so teams can focus on higher-value work.