The big picture: The technology job market in 2025 is seeing a surge in new opportunities, yet it’s also rife with confusion. As artificial intelligence rapidly expands across industries, companies scramble to integrate it into their operations. Job seekers are left navigating a maze of titles that often appear interchangeable but lack clear definitions.
Karin Kimbrough, LinkedIn’s chief global economist, explained that the tech industry now assigns up to 40 different titles to similar roles, leaving job seekers uncertain about whether one position is the same as another. She noted this confusion in an interview with the Wall Street Journal. This ambiguity is widespread, with similar roles at different organizations labeled as “AI engineer,” “machine learning developer,” or “data architect,” often with additional qualifiers like “senior,” “associate,” or “specialist.”
This explosion of titles stems directly from the AI boom. Research by the University of Maryland and job-tracking firm LinkUp, part of the UMD-LinkUp AI Maps project, reveals that nearly a quarter of new tech jobs in the United States this year seek candidates with artificial intelligence skills. Companies are eager to find talent capable of driving their AI initiatives. Still, the lack of standardization in job titles makes it more difficult for employers and applicants to connect.
Job seekers have found this trend increasingly frustrating as companies continue adding new positions. Jack McVickar has been searching for work since being laid off from an IT services company and has experienced the shift firsthand. He told the Wall Street Journal that “the titles are all over the place,” adding that he now analyzes keywords and contacts company representatives to better understand what each job posting actually entails.
The challenge extends beyond job seekers. Employers face difficulty striking the right balance between specificity and flexibility in their job postings. They aim to create appealing, targeted titles that remain adaptable as technology and business needs evolve.
Don Vu, chief data and analytics officer at New York Life, noted that this territory is uncharted for many organizations. With no clear precedent for new titles, human resources representatives find it challenging to place accurate career ads.
“This is all still very much nascent and developing,” Vu explains. “Is this an AI manager? Is it an AI coding agent? Is it an AI coding agent manager? There’s a lot of new titles that didn’t exist before that are now manifesting.”
His team often looks to leading tech companies for inspiration, hoping that using familiar titles will help position them as forward-thinking in the eyes of candidates. Meanwhile, job roles continue to evolve. Vu notes that the traditional data scientist position is gradually shifting toward something closer to an AI engineer, requiring more advanced software development skills. However, he cautions that many companies have yet to determine how to structure these roles or whether to retrain existing staff or hire new talent.
Despite the confusion, demand for AI talent remains strong. LinkedIn reports that professionals with AI expertise secure jobs 30 percent faster than others. The market for software engineers has shifted, with postings for those roles shrinking as a share of total tech jobs. Meanwhile, listings for AI and machine learning engineers – once too rare to register – now represent a noticeable portion of openings.
Karin Kimbrough, LinkedIn’s chief global economist, notes that while technology job titles have continually evolved, the current pace of change is unprecedented. She told the Wall Street Journal that LinkedIn data shows about 20 percent of Americans who started a new job in the past year hold titles that did not exist at the start of the century. Kimbrough called the trend “pretty stunning.”