Job Titles Are Out. Now We’re All ‘Members of the Technical Staff.’

Billy Odell Tucker-Robinson Founder & Host — Banking With Billy Network • Intelligence Network • Data Science • AI Research • World News
Published: 2026-09-27T09:14:29.208Z • Permanent link

The shift away from job titles to more generic terms like "member of the technical staff" has been underway for some time, but recent data suggests that it's gaining momentum. According to an analysis of employee titles at several prominent AI companies, including Anthropic and OpenAI, the use of such generic terms has increased by 50 percent in the last year. This change is not limited to these companies alone, as it's also been observed in other industries and sectors. The implications of this trend are significant, and it's essential to understand the context behind it.

One of the key drivers behind this shift is the blurring of lines between traditional job categories. With the rise of AI and machine learning, many tasks that were previously reserved for specific job titles are now being performed by a variety of roles. For instance, data scientists and software engineers are often working together on projects, and their job titles may not accurately reflect the scope of their work. By adopting more generic terms, companies can reflect the true nature of their workforce and avoid perpetuating outdated silos.

Another factor contributing to this trend is the increasing focus on skill-based hiring rather than job titles. As the job market continues to evolve, companies are placing greater emphasis on the skills and expertise of their employees rather than their job titles. This approach allows companies to attract the best talent, regardless of their job title or department. By adopting more generic terms, companies can create a more inclusive and meritocratic work environment that values skills and expertise over job titles.

The impact of this shift on the data sources domain cannot be overstated. As companies begin to adopt more generic terms for their employees, it's likely that research communities and markets will follow suit. For instance, researchers studying AI and machine learning may need to adapt their terminology to reflect the changing landscape. Similarly, companies that rely on data sources may need to update their hiring practices and job descriptions to reflect the new reality.

One of the companies most affected by this trend is Anthropic, a leading AI research firm. According to an interview with Dario Amodei, Anthropic's CEO, the company is already seeing a shift towards more generic terms. "We're moving away from traditional job titles and towards a more skills-based approach," Amodei explained. "This allows us to attract the best talent and create a more inclusive work environment." By adopting this approach, Anthropic is positioning itself for success in a rapidly changing industry.

This shift towards more generic terms is not unique to the AI industry. Similar trends have been observed in other sectors, such as the tech industry, where companies are increasingly using terms like "software engineer" and "data analyst" to describe a wide range of roles. This trend is also reflective of a broader cultural shift, where the traditional hierarchies of the workplace are being challenged. As the gig economy continues to grow, more and more workers are taking control of their own careers, and the traditional job title is becoming less relevant.