Skill-first job matching for KAU IT graduates
The Problem
KAU IT graduates leave university with strong technical skills but no public footprint. Existing job platforms reward profile completeness — which new graduates don't have — so they get filtered out before a recruiter ever sees them. KAUGrads flips the model: start with what you know, not what you've done.
The goal was a fully-bilingual (Arabic / English) platform prototype that surfaces candidates to employers through a skill-first match flow, with transparent scoring and a 30-second time-to-first-match.
Design
The cold-start UX problem for a job-matching platform is real: new graduates have nothing to show. I led with a chip-based skill picker (3–7 chips) before any résumé upload, so the first match could land within 30 seconds of landing on the page. The résumé came later, as enrichment — not as a gate.
Twelve fully-linked screens with realistic data, an interactive prototype flow, and a component library. The artefact was designed to be demoed to stakeholders, not explained. Every screen was bilingual from day one — the same frame flipped direction without rebuilding.
Arabic users are the primary audience, so RTL was the first layout pass — not a translation. Spacing, type scale, and component density were calibrated for both directions before any final pixel work, which kept the prototype visually balanced in either language.
Screens
Outcome
Designed and prototyped KAUGrads as a 12-screen Figma deliverable: a skill-first onboarding flow, graduate dashboard with match rankings, transparent match-detail scoring, and a full Arabic RTL pass on every screen. The prototype was presented as a clickable demo with realistic data — ready to be handed off to engineering.