Saving job seekers 40 hours/week using personalized AI job-matching
Reduced search time from 10–40 hours to minutes while validating a new monetization channel through early paid conversion.
Job seekers were spending 10–40 hours a week searching, filtering, and applying manually. Wellfound needed a breakthrough product that dramatically simplified the process while opening a new B2C monetization stream.
As Lead Product Designer, I partnered with the PM to take Raven from concept to launch. Raven is an AI-powered, personalized, job search agent that scans the web, surfaces matching roles, provides match insights, and tailors resumes—reducing job-seeking time from 10–40 hours a week to just minutes.
1,600+
Provided signal density for activation patterns and PMF during early beta.
100+
Paid subscribers validated a consumer monetization opportunity for Wellfound.
10–40 hrs
Raven automated job search and matching, reducing cognitive load and time cost.
10k+
Scaled user growth positioned Raven as a long-term addition to the candidate experience
Reduce job-seeking time by more than 80 percent and validate willingness to pay for an AI-driven job search experience.
We believed that automating the most time-consuming aspects of job searching—discovery, personalization, and application prep—would create a more engaging and valuable experience for job seekers.
I led the end-to-end product design process, from user research and UX/UI to brand identity and launch assets. Working closely with the PM, we defined the product strategy, built prototypes for validation, and ran experiments to test early monetization through pricing A/B tests.
The beta launched to 1,600+ users with strong engagement. A pricing experiment ($5.99 vs. $9.99 between a 7-day or 14-day trial) revealed greater urgency and adoption within shorter trial periods for extended product value. The beta yielded 100+ paid conversions despite little to no marketing — indicating early product value and user willingness to pay.
The beta validated early demand for personalized search experiences and monetization potential, uncovering user segments and behaviors that now inform future iterations. Raven continues to evolve as part of Wellfound’s AI suite, serving as the foundation for smarter, more personalized candidate experiences.
1,600+
Provided signal density for activation patterns and PMF during early beta.
100+
Paid subscribers validated a consumer monetization opportunity for Wellfound.
10–40 hrs
Raven automated job search and matching, reducing cognitive load and time cost.
10k+
Scaled user growth positioned Raven as a long-term addition to the candidate experience
