In 2025, the QA engineer job market is undergoing a transformation. According to the LinkedIn Work-Change Report, since 2023, the number of users who added AI skills to their profiles has increased by 177%. This is nearly five times faster than the growth of other skills (+36%). At the same time, the demand for specialists with AI competencies has grown 30% faster than the overall hiring market.
According to the LinkedIn Jobs on the Rise (2025) report, half of AI-related professions did not even exist 25 years ago, and today — they are among the most dynamic fields in the world. Among the fastest-growing are AI Engineer and AI Consultant. Axios analytics adds: in 2024, the number of AI-related job postings on LinkedIn increased by 59%, despite the overall decline in technical positions.
Experts explain: today, companies need more than just a “bug hunter.” They need engineers capable of integrating AI into processes, optimizing test scenarios, and at the same time thinking strategically. One of the experts confirming this trend is Yuliia Baranetska — Senior Automation QA Engineer at Playtika. From her, we will learn what a QA engineer needs to know in 2025.
“Yuliia is the most qualified and dedicated QA engineer I have ever worked with. She is capable of building processes from scratch and dives deeply into the subject area,” says Dmytro Kovalov, one of the industry leaders who has worked in IT since 2002 and was her manager at Datas Technology.
Yuliia Baranetska’s professional experience covers automation, Big Data, and work in international companies with millions of users. She is the author of blogs on Hashnode, Medium, and DOU.ua, a mentor on Exercism.org, and a consultant at codereview.stackexchange.com. In her articles, Yuliia focuses on the impact of AI and shares analytics about what QA engineers need to know to remain competitive.
“I have seen Yuliia not only demonstrate high technical expertise but also unite the team around common goals. This is a unique trait that has made her a key figure in Playtika’s automated testing structure,” adds Dmytro Petrovskyi, R\&D Group Manager at Playtika.
Market analysis and expert commentary highlight several key directions. These are confirmed and commented on by Yuliia Baranetska.
Today the market is evolving in such a way that the boundaries between programming languages are becoming significantly blurred.
“Thanks to tools like Selenium, Playwright, Appium, or Selenide, today you can build test architecture even without deep knowledge of every language,” notes Yuliia. “This lowers the entry barrier while increasing the requirements for understanding test architecture as a whole.”
Today the speed requirements have increased. If earlier the creation of test scenarios could take days, now it is not uncommon for test results to be expected almost in real time.
“Companies expect engineers to be able to work with scenario generation and self-healing tests,” explains Yuliia. “And those who can integrate AI into this process gain a significant advantage.”
The range of areas a specialist should be familiar with is constantly expanding.
“Today, without CI/CD, Docker, and Kubernetes, a QA becomes less competitive. This is no longer an extra advantage, but a basic standard,” Yuliia emphasizes.
Despite the involvement of AI, the human factor does not disappear.
“An algorithm can suggest a test, but it cannot assess the business value of a technical solution,” comments Yuliia. “A QA must look beyond the code — at user experience, financial risks, and long-term strategy.”
“This is something AI cannot replace and something that will always be at the top. The ability to explain, teach, and build trust within a team are key skills for a modern QA,” says Yuliia. And she concludes: “It is precisely thanks to soft skills that we can turn tests into tools for product growth, not just quality control.”
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