The Brief

Job search apps tend to optimize for listing volume, not relevance — the result is a firehose of postings a candidate has to manually filter. AI Smart Job Finder was built around the opposite bet: fewer, better-matched results, using AI to do the matching work a job seeker would otherwise do manually across a dozen browser tabs.

The Approach

The development workflow used AI-assisted scaffolding and iteration around the app's matching and recommendation experience. The product goal is helping a job seeker interpret relevance, not claiming that an AI recommendation guarantees employment.

Where AI Fit In

AI is used in the matching layer: interpreting a candidate's profile and preferences against available listings to surface relevance, rather than presenting a raw, unranked feed. As with any AI-assisted recommendation system, the design goal was to keep the logic legible — showing why a match was suggested — rather than a black-box score.

The Outcome

AI Smart Job Finder is published on Google Play under the Zaidan Lab developer account. Alongside Kalori AI, it demonstrates how a bounded AI feature can be incorporated into an accessible mobile product. It remains distinct from JobAI Web and CV Job Matcher.