# I got tired of losing good jobs to timing, so I built a pipeline that scores LinkedIn listings against my CV and emails me the best matches

> Source: <https://dev.to/tdk99/i-got-tired-of-losing-good-jobs-to-timing-so-i-built-a-pipeline-that-scores-linkedin-listings-5p8>
> Published: 2026-09-07 19:06:54+00:00

A job posting gets 200+ applicants in 48 hours. By the time LinkedIn's daily digest hits your inbox, the window is already closing.

I kept finding great matches days after they were posted. So I built SnapplAI: it scrapes fresh LinkedIn listings, sends each one to Gemini to score it against your CV, and emails you only the top matches, before the crowd even sees them.

**How it works**

Four steps, one pandas DataFrame, no frameworks:

Scrape — fresh listings from LinkedIn based on your filters

Summarize — Gemini extracts structured fields as JSON

Analyze — each listing scored against your CV (chain-of-thought enforced: reasoning before judgment)

Deliver — top matches emailed to your inbox

Runs locally, via Docker, or as a scheduled GitHub Actions cron. Full setup takes 5 minutes.

**Why no framework**

I wanted a clean data pipeline with LLM calls where they matter, not an agent framework. Python orchestrates, AI evaluates. Each Gemini call retries with exponential backoff and falls back through a model chain, so a throttled API doesn't crash the run.

**Try it**

MIT-licensed. Issues, PRs, and forks are welcome.