AI-Powered Career Accelerator & Smart Resume Matcher

An intelligent talent acquisition and career progression engine featuring automated multi-format CV extraction, semantic role matching, and personalized skill-gap progression pathways powered by LLMs.

Project Overview

Modern recruitment pipelines face a dual bottleneck: hiring teams drown in hundreds of unstructured PDF resumes with low-accuracy keyword filters, while job seekers lack objective feedback on why their applications don't advance and how to upskill effectively.

I developed the AI-Powered Career Accelerator to bridge this gap. Candidates upload resumes in any format (PDF, DOCX) and receive a comprehensive semantic audit: matched job descriptions, quantitative compatibility scoring, missing competencies, and tailored weekly study recommendations.

Core Challenges & Architectural Solutions

• Semantic Embedding Pipeline: Implemented OpenAI text embeddings and vector search in Qdrant, transitioning candidate scoring from brittle keyword matches to deep contextual capability appraisal.
• Multi-Format CV Parsing Engine: Built an asynchronous FastAPI pipeline that parses complex multi-column PDF layouts, sanitizes OCR noise, and maps experience chronologies accurately.
• Automated Roadmap Synthesizer: Created dynamic prompt chains that analyze target job requirements against current candidate portfolios, spitting out step-by-step project-based learning roadmaps.