AI-Powered Candidate Screening and Ranking Pipeline

Overview

Screening hundreds of resumes manually is slow and inconsistent. This workflow uses n8n and OpenAI to build an automated candidate screening pipeline that evaluates resumes against job requirements, scores candidates, and surfaces the top matches.

Steps

1. Define scoring criteria: Create a structured rubric with must-have qualifications, preferred skills, experience levels, and weighted scoring for each criterion.
2. Set up the n8n workflow: Build a workflow that ingests resumes (from email, ATS export, or shared folder) and passes them to OpenAI for analysis.
3. Configure AI evaluation: Prompt OpenAI to evaluate each resume against your rubric, scoring on each criterion and providing a brief rationale for each score.
4. Rank and filter: Sort candidates by total score, filter by minimum thresholds on must-have criteria, and output a ranked shortlist.
5. Review and act: Human recruiter reviews the shortlist, verifies AI reasoning, and moves qualified candidates to the interview stage.

What you'll learn

• Building fair, consistent screening criteria for AI evaluation
• n8n automation patterns for HR workflows
• How to maintain human oversight while scaling screening volume