The listing pool should be usable.
People make better decisions when the underlying data is current, portable, and available across more than one interface.
About the team
We want the job market to be easier to work with.
MeWannaJob is built by a team of dedicated engineers who think job search should feel less like wandering through stale listings and more like working with a clear, current market map.
We build tools that turn open job data into practical next steps: ranked apply plans, mobile-first job browsing, dashboard comparisons, and research views that make skill demand easier to understand.
What we care about
Engineering values for job search.
The fastest path should be the strongest one.
For most users, the first win is a ranked apply plan. The product should get them there before asking them to manage a dashboard.
The deeper views should hold up.
Researchers and power users need repeatable comparisons by skill, company, industry, location, seniority, and time.
Why we built it
The job market is noisy. The data does not have to be.
Get from listing overload to a plan.
Upload a resume and the job CSV to ChatGPT, then ask for fit scores, missing skills, outreach messages, and a focused weekly plan.
Compare demand instead of vibes.
Use the same pool to inspect skill pressure across industries, regional demand, company hiring patterns, and role clusters.
Treat job listings like product data.
The RFC topology separates the consumer surface from the canonical data layer, which keeps product pages cleaner and data contracts easier to reason about.
The team promise
We are building toward a job market people can interrogate, not just endure.
The MeWannaJob team is small, engineering-heavy, and stubborn about reducing friction. We care about search surfaces that respect the user's time, data workflows that can be audited, and product design that helps people make decisions instead of simply adding another feed.