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ApplyKit

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Automated job discovery pipeline. Aggregates listings, scores JD to Resme fit, and generates gap mitigation strategies with AI-assisted research.

ApplyKit screenshot
Splash screen of ApplyKit

// summary

Job search is repetitive work: find listings, filter by relevance, research each company, tailor a resume, prepare for interviews. ApplyKit automates the pipeline from discovery to preparation.

The system aggregates job listings from multiple sources, scores each against a configurable fit profile (skills, seniority, role type, location), and surfaces the best matches. For shortlisted roles, it runs LLM assisted profile analysis and generates gap mitigation plan.

Built for my own job search, then generalized. The scraping layer handles the inconsistency of job board markup; the scoring layer is tunable without code changes; the job pipeline output is structured enough to actually use for job funnel tracking.

// tech stack

Language

Typescript

TUI

Opentui

Data

Web Scraping

AI / ML

LLM Scoring AI Research

Systems

Automation