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CareerKor Platform

An enterprise-grade AI ecosystem designed to bridge the gap between job seekers and Applicant Tracking Systems (ATS).

User Engagement500+

Active monthly users optimized

Engine Performance16ms

Real-time UI state re-renders

AI Optimization35%

Avg. ATS score improvement

The Engineering Challenge

Modern Applicant Tracking Systems (ATS) use complex parsing logic to filter candidates. Job seekers often fail not due to lack of skill, but because of poor formatting and keyword density.

The objective was to build a platform that could simulate these ATS engines in real-time, providing job seekers with a "score" and actionable suggestions as they type their resume.

Architectural Solutions

Normalized Redux State

Managing a complex, nested resume structure (education, experience, skills) required a highly optimized state management strategy. By normalizing the data, we achieved O(1) lookups and sub-16ms update cycles, ensuring no input lag during intensive AI scoring.

Custom SSR PDF Pipeline

Most PDF libraries generate non-selectable text or unparsed structures. I developed a specialized SSR pipeline using Puppeteer and CSS print-media queries that renders the React UI into high-fidelity, machine-parseable PDFs that pass 100% of ATS validation tests.

Development Outcome

  • Successfully launched to production with 500+ organic users.
  • Achieved 95+ Lighthouse accessibility scores on all core pages.
  • Implemented a secure, role-based user authentication system.
  • Seamlessly integrated OpenAI's GPT-4 for granular resume suggestions.

Technical Stack

React 18Node.jsRedux ToolkitTailwind CSSOpenAIPuppeteerPostgreSQL
Real-time Data Syncing
Enterprise Security (JWT)
Custom Design System

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