A year ago, Jooble launched Fitly, an AI-powered service that helps candidates search for jobs, tailor their resumes to specific vacancies, and apply for positions faster. Over a million people have used the product in the past year, and MRR has grown 10x.
A year ago, Jooble launched Fitly, an AI-powered service that helps candidates search for jobs, tailor their resumes to specific vacancies, and apply for positions faster. Over a million people have used the product in the past year, and MRR has grown 10x.
A small AI-native team is working on Fitly. Head of New Products at Jooble Oleksiy Rubanyak told dev.ua how the team approaches the development of the service, why one AI resume generator is not enough, and how they are trying to automate the entire candidate journey — from job search to response.
At the start, Fitly solved a very specific problem — helping candidates adapt their resume to the job vacancy. But it quickly became clear that editing a CV by itself did not solve the user’s main problem.
“You can make a very good resume, but if a person spends hours searching for vacancies, then manually writes a Cover Letter and fills out dozens of identical forms, the problem does not go away,” explains Rubaniak.
Therefore, the team gradually expanded the product. Now Fitly combines job search, candidate suitability analysis, resume adaptation, cover letter generation, and tools for faster application submission.
One of the basic functions is CV Tailoring. The system analyzes the description of a specific vacancy and adapts the candidate’s resume to it, including taking into account relevant keywords that ATS may pay attention to.
“Our task is not to simply rewrite the resume with prettier words. It is important to understand what exactly is required for this vacancy, what skills are relevant, and how to show the candidate’s relevant experience,” says Rubaniak.
Separately, the service allows you to create a Cover Letter for a specific position in one click.
Another area that the team is developing after talking to users is skill-based search.
The problem is that job titles don’t always accurately describe a person’s actual skill set. A professional may have experience that fits multiple types of positions, even though they haven’t had a job title that literally matches their previous experience.
Therefore, the team rewrote the job matching logic and added search by skills.
“We want to move away from the logic of ‘you have the same job title, so the vacancy suits you.’ It is much more important to understand what a person is capable of and what experience they have,” explains Rubaniak.
This is reflected in the product itself, in particular, through Match Score, an assessment of the candidate’s suitability for a specific vacancy.
Even after a candidate has found a relevant position and adapted their CV, there is still one more stage left — submitting an application.
"We saw that people are willing to spend a lot of time on mechanical actions. Open a vacancy, go to another site, fill in the same fields, attach a resume, indicate experience again. This is not the kind of work that the candidate wants to do," says Rubaniak.
That’s why Fitly has a Chrome extension with auto-fill for job forms.
The idea is to reduce the amount of manual work and leave the candidate more time for what really requires their participation.
What conversations with users showed
The team uses user feedback not only to find bugs or minor improvements. CustDev interviews have become one of the sources for new features.
This is how Fitly introduced Job Tracker, a tool for tracking vacancies and review statuses.
“People often don’t remember where they applied. Especially when the job search lasts several weeks or months. That’s why we added the ability to see this process as a funnel,” says Rubaniak.
At the same time, the team updated onboarding and matching logic. According to the company, these changes had a positive impact on retention and churn.
Over the year of the product’s operation, the team also received interesting data about user behavior.
Fitly’s largest audience is in the United States, followed by Poland, France, Germany, Italy, the United Kingdom, and Spain. In total, the service is used in 95 countries.
One of the most interesting metrics is conversion by job type. 78% of users searching for the position “director” become paying customers. For the query “customer service”, this figure is 25%.
Another insight is about age. 86% of Fitly’s subscribers in the US are aged 45+. Their median professional experience is 10 years.
“This was an important discovery for us. We are not building a product exclusively for people looking for their first job. A significant part of the paid audience is experienced professionals who are interested in reducing their search time and making it more efficient,” says Rubaniak.
The team also saw that job searches have a pronounced work schedule: 77% of onboardings occur Monday–Friday, with the peak occurring on Tuesday.
Two engineers and a performance marketer work on Fitly.
The team actively uses AI agents in their own work. They are used for prototyping, design, analytics, and automation of other processes.
“We don’t perceive AI as a separate feature of the product. For us, it is also a tool with which we build the product ourselves. Everyone on the team uses several AI agents in their work,” says Rubaniak.
According to him, this allows a small team to work much faster.
Fitly has attracted over a million users in its first year and MRR has grown 10x. The team has also improved unit economics and is preparing to scale the main acquisition channel through Meta, while simultaneously testing new channels on Jooble and Google.
“At this stage, it’s important for us not just to attract more people. We want to understand which job search scenarios provide the most value to the user and how to make this path as short as possible,” says Rubaniak.
The Fitly team is also currently looking for a Senior Product Manager who will work with paid channels, hypothesis testing, and product scaling.
