AI was supposed to kill engineering jobs, but new data suggests they’re the most resilient

New hiring data is complicating one of tech's most persistent narratives: that artificial intelligence is quietly hollowing out the software engineering profession. Research from venture capital firm SignalFire indicates that engineers now represent a growing proportion of newly hired tech workers, even as executives and headlines continue to frame coding roles as prime candidates for automation.

The contradiction is striking given the backdrop. Layoffs across the technology sector spiked in May, reaching their highest monthly total in several years, according to tracking from outplacement firm Challenger, Gray & Christmas. Employers most frequently pointed to artificial intelligence as the driving factor behind those job cuts, reinforcing widespread anxiety that AI tools were finally displacing human workers at scale.

That anxiety has focused heavily on software developers specifically. The logic seemed straightforward: as AI-assisted coding platforms grew more capable and were adopted faster than almost any other workplace technology, engineering appeared to be the occupation with the clearest exposure to automation. If AI could write, debug, and ship code, the reasoning went, companies would need fewer human programmers to do the same work.

SignalFire's analysts, however, say the actual hiring patterns tell a different story than the layoff headlines suggest. Rather than shrinking as a share of the workforce being brought on, engineers are claiming more of the hiring pie, not less. The firm's data implies that demand for engineering talent has held up, or even strengthened, at the same time that AI-related job cuts have been grabbing attention elsewhere in the industry.

Several forces could explain the gap between perception and data. Building, deploying, and maintaining AI systems themselves requires substantial engineering talent, meaning the AI boom may be generating as much demand for developers as it displaces. There is also a case that AI coding assistants function more as productivity multipliers than replacements, letting existing engineers accomplish more without necessarily shrinking the need for new hires. Companies racing to ship AI-powered products may simply need more builders, not fewer.

Still, the SignalFire findings do not erase the reality reflected in the Challenger, Gray & Christmas figures. Layoffs tied to AI were real and numerous enough to produce the worst monthly total the tech sector has seen in years, suggesting that whatever resilience engineering roles are showing in aggregate hiring, individual companies and specific functions within engineering may still be shedding jobs. Roles considered more repetitive or easily automated, such as certain testing or lower-level coding tasks, could be more exposed than the broader hiring trend implies.

The divergence underscores how difficult it remains to draw firm conclusions about AI's net effect on employment from any single data source. Hiring totals capture who is being added, while layoff tallies capture who is being cut, and the two can move in different directions across different segments of the same workforce simultaneously. As more employment data accumulates through the rest of the year, researchers and labor economists are likely to keep testing whether engineering's apparent resilience holds up or proves to be a temporary artifact of an industry still figuring out how to integrate AI into its workflows.

Source: TechCrunch