Gemini AI Resume Screener

I need a web-based application that taps into Gemini AI to automate the most time-consuming part of hiring: screening incoming resumes. The core of the build is a smart filter that can instantly parse an uploaded PDF, DOCX, or LinkedIn export, run keyword matching, gauge overall experience level, and score demonstrated skills against a role profile I define.

Key flow
• Recruiter uploads one résumé or an entire folder.
• Gemini analyzes each document, tags relevant keywords, measures years of experience per skill, and produces an overall fit score.
• A results page ranks candidates, lets me drill into AI-generated rationale, and allows CSV export or direct push to an ATS through REST endpoints.

I only need the resume-screening module for now—interview scheduling and other add-ons can wait—so the interface can stay lean: React or Vue front-end, a lightweight Node or Python API layer, Gemini API calls behind the scenes, and a small Postgres (or similar) database to cache results and role templates. If you have a different but equally efficient stack in mind, I’m open, as long as the final product stays web-based and easy to host on AWS or GCP.

Deliverables
• Source-controlled codebase with clear README
• Deployed demo on a cloud free tier (or my own server)
• Brief video walk-through and PDF user guide
• One round of post-delivery tweaks to polish UX or scoring logic

Acceptance criteria
1. Upload of at least 50 resumes completes in under 2 minutes.
2. Keyword, experience, and skill scores match a provided test set ±5 %.
3. UI renders cleanly on Chrome, Firefox, Safari, and Edge.

If this sounds like your field, let’s discuss timeline and milestones so we can get the screener live soon.