Build an AI-powered recruitment assistant using Amazon Bedrock

This article demonstrates how to build an AI-powered recruitment assistant using Amazon Bedrock to automate candidate screening, scoring, and interview preparation.

• Recruiters spend 17.7 hours per vacancy on administrative work; 45% spend over half their time on automatable tasks
• Solution uses Amazon Bedrock Converse API with Amazon Nova Pro for resume analysis and candidate matching
• Intelligent resume analysis calculates compatibility scores with specific evidence from resume text
• Personalized interview questions generated based on job requirements and candidate backgrounds
• Amazon Bedrock Guardrails provide PII anonymization, prompt injection detection, and bias filtering
• Architecture includes AWS Amplify frontend, Amazon Cognito authentication, API Gateway, Lambda, DynamoDB, and S3
• Estimated cost for testing with 100 candidates: approximately $1–2 per month
• Security controls include S3 Block Public Access, encryption at rest, API throttling, and least-privilege IAM policies
• Production deployment requires additional considerations: AWS WAF, CloudWatch monitoring, data lifecycle automation, and fairness testing
• Solution extensible for multi-turn conversations, AI-assisted outreach, and bias auditing dashboards

This reference architecture demonstrates how to leverage generative AI to reduce recruiter administrative burden while maintaining human oversight in hiring decisions.