Manual job searching at scale means hours spent cross-referencing hundreds of postings against a single CV — a process prone to bias, fatigue, and missed signals. There was no tooling to make this systematic.

Design and ship a fully automated AI screening pipeline that evaluates job-CV compatibility objectively, ranks opportunities by fit, and eliminates the noise from manual review — built entirely independently, from scratch.

Architected an end-to-end automation pipeline on n8n, integrating Supabase for structured data persistence and PostgreSQL querying. Developed custom Python scoring logic and wired Gemini AI for semantic match analysis across structured vacancy data. The system parses, scores, and stores results automatically.

Deployed a production-grade HR assistant that has processed 100+ job applications — reducing per-application analysis time from hours to under a minute. Compatibility reports are generated automatically, enabling a data-driven, high-signal approach to career decisions.