Job Apps Automation v1
AI-powered job application assistant that parses job descriptions and generates tailored materials
Tech Stack
Overview
AutoApply takes a raw job posting, extracts structured data (company, role, tech stack, qualifications), then generates targeted resume bullets and a full cover letter matched to the position — all powered by GPT-4 Turbo and LangChain.
The tool features a dark Catppuccin-themed PyQt5 interface with three tabs: Job Parser, Resume Bullets, and Cover Letter. Paste any job description and it instantly extracts structured JSON with company info, responsibilities, tech stack, qualifications, compensation, and location. The resume bullet generator uses Pinecone vector search to semantically match your experience against the specific role requirements.
Screenshots
Job Parser — Stripe posting parsed into structured JSON
Resume Bullets — Tailored for Senior SWE @ Stripe
Key Features
Job Parser
Paste any job description and get structured JSON with company info, responsibilities, tech stack, qualifications, compensation, and location.
Resume Bullet Generator
Produces tailored achievement bullets matched to the specific role and tech requirements using semantic vector search against your experience.
Cover Letter Writer
Generates a complete, personalized cover letter referencing the parsed job details, company mission, and your matched qualifications.
Vector Resume Search
Pinecone-powered semantic matching against your experience. Finds the most relevant achievements from your history for each job.
Architecture
AutoApply is a desktop application built with PyQt5 and a dark Catppuccin theme. The AI pipeline uses LangChain to orchestrate GPT-4 Turbo calls for parsing, bullet generation, and cover letter writing. Pinecone provides the vector store for semantic resume matching, and SerpAPI enables job discovery.
The parsing pipeline extracts structured data from free-text job descriptions, then uses that structured output as context for generating highly targeted application materials.