Streamlining Recruitment Through GenAI and Cloud-Native Automation

About Client:

A leading healthcare organization focused on modernizing its recruitment operations and enhancing efficiency across high-volume roles. The client is recognized for its strong commitment to workforce excellence and continuous process innovation within the healthcare sector.

Background:

The client faced growing inefficiencies in their hiring process, as thousands of applications for each role made it difficult for recruiters to efficiently identify and engage the right talent. The manual, time-intensive screening approach led to delayed hiring cycles, inconsistent candidate evaluations, and a higher likelihood of missing qualified candidates — ultimately impacting overall recruitment effectiveness and workforce planning.

Challenge:

The client faced multiple hurdles in streamlining their recruitment process:

  • High resume volumes made manual shortlisting time-consuming and inconsistent.
  • Unstructured resume data (varying formats, incomplete fields) hampered effective comparison.
  • Contextual understanding gaps in traditional keyword-based systems led to poor matching of candidates with transferable skills or synonymous experience.
  • Limited recruiter bandwidth restricted personalized candidate engagement and assessments.

Solution:

The client’s hiring process was transformed through AROMA— a GenAI-powered recruitment automation platform that digitizes and optimizes every stage of recruitment, from resume intake to interview management.

Phase 1: Secure Resume & JD Ingestion

Recruiters can upload job descriptions and resumes via the AROMA web app or a designated Google Drive folder.

  • Integrated with Google Drive API for automatic document synchronization.
  • Files are validated and securely stored in AWS S3, with metadata logged in AWS RDS (PostgreSQL + PGVector).
  • The backend, built on FastAPI, manages structured mapping between jobs and candidate profiles.
  • The system is hosted on AWS EC2, running a Dockerized deployment pipeline that is automatically built and deployed through GitHub Actions.

Phase 2: Resume Parsing & Data Structuring

A Python-based pipeline standardizes different file formats (PDF, DOCX, TXT) and extracts key candidate details.

  • Uses regex, spaCy NLP, and custom parsing logic for entity extraction.
  • Parsed data is normalized and transformed into structured profiles ready for semantic analysis.

Phase 3: AI-Powered Matching & Ranking

LLMs via Amazon Bedrock enable intelligent, context-aware matching between resumes and job descriptions.

  • Performs semantic similarity and zero-shot classification to evaluate skill and experience relevance.
  • Generates contextual match scores based on role fit, skill overlap, and experience alignment.
  • A vector-based RAG layer enhances contextual understanding of candidate–role compatibility.

Phase 4: Chatbot & Interview Automation

A GenAI chatbot, powered by Bedrock Agents, engages candidates for Q&A, pre-screening, and interview preparation.

  • Integrates with Google Calendar for interview scheduling and management.
  • Candidate interactions and summaries are logged in AWS CloudWatch for visibility and compliance.

Phase 5: Monitoring & Continuous Optimization

  • AWS CloudWatch monitors all activities — uploads, parsing, matching, and chatbot sessions.
  • Recruiter feedback is used to refine ranking logic and improve LLM prompt templates.
  • The modular architecture supports easy scaling across departments and multiple hiring pipelines.

Outcome:

The implementation of AROMA significantly transformed the client’s recruitment operations, delivering measurable efficiency and accuracy gains across the hiring lifecycle.

  • 75% reduction in manual resume screening time.
  • Improved candidate-to-role matching accuracy compared to keyword-based systems.
  • End-to-end automation across the hiring process — from resume intake to onboarding to 1-2 weeks.
  • Enhanced recruiter productivity and data-driven decision-making through centralized analytics.
  • Scalable, cloud-native platform supporting large hiring pipelines with minimal manual effort.

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