AI Job Threat Reversed: Engineers Prove Most Resilient

The extent to which artificial intelligence is currently displacing jobs remains a topic of intense discussion and disagreement.

In May, the technology sector experienced its highest monthly total of layoffs in several years, with AI frequently cited as the primary contributing factor, as reported by the outplacement firm Challenger, Gray & Christmas.

While software engineering is theoretically considered the professional domain most susceptible to automation, primarily due to the swift integration of AI-driven coding tools, analysis from researchers at the venture firm SignalFire suggests that actual hiring data presents an alternative narrative.

Asher Bantock, SignalFire’s head of research, noted, “The rationale given for lots of layoffs is consistently AI, and specifically they’ll say AI with respect to code; they’ll say one engineer could do the job of however many engineers in the past.” He further indicated that “What we’re seeing on the ground is a little inconsistent with that.”

SignalFire’s comprehensive analysis, which encompassed the career trajectories of millions of employees across over 80 million companies, posited engineering as the most resilient job function in 2025. The firm opted to scrutinize hiring data as a more precise gauge of real-time workforce dynamics, rather than focusing on layoffs, which are often challenging to track due to delays in employment status updates post-job cuts.

According to SignalFire’s most recent “State of Talent Report,” although overall hiring across major tech corporations decreased by 25% compared to 2019 figures, engineering positions experienced a considerably smaller reduction of only 11%.

Indeed, engineers constituted 55% of all new recruits in 2025 across the twelve companies designated as “Tech Majors” by SignalFire—Alphabet, Meta, Apple, Amazon, Microsoft, Netflix, NVIDIA, Tesla, Uber, Airbnb, Block, and Stripe. This marks a notable increase from 2019, when engineers accounted for just 46% of new hires, the report indicates.

The persistent demand for engineering talent was even more pronounced within early-stage startups, which collectively onboarded 7% more engineers in 2025 than in 2019, as demonstrated by SignalFire’s data.

Bantock contended that if AI were genuinely replacing engineering talent, hiring for engineering roles would be the first to decline during the ongoing contraction in tech hiring. However, SignalFire’s data reveals that engineering headcount is expanding at a faster rate than the majority of other job functions within the tech industry.

Despite a warning last year from Anthropic CEO Dario Amodei that AI could eliminate half of all entry-level white-collar positions and elevate unemployment to 20% within five years, Peter McCrory, the company’s own head of economics, informed TechCrunch in March that he has not yet observed any substantial AI-induced impacts on the workforce.

McCrory stated at the time, “There’s at least no larger material difference in unemployment rates” when comparing workers who utilize AI tools like Claude for the “most central task of their job in automated ways”—such as technical writers, data entry clerks, and software engineers—and those employed in roles less exposed to AI, which demand “physical interaction and dexterity with the real world.”

Nvidia CEO Jensen Huang took an even stronger stance, unequivocally dismissing the notion that AI will supplant engineers. During an interview at the Stanford Graduate School of Business in April, Huang remarked, “Somebody said that AI is going to destroy all of the software engineering jobs.” He posited the contrary, asserting that with all Nvidia engineers now leveraging agentic AI, “software engineers are busier than ever.”

Huang elaborated that while AI agents are capable of generating code almost instantaneously, they continuously challenge engineers to conceive and develop “the next idea.”

At present, it appears that, equipped with AI, engineering has emerged as a quintessential illustration of the Jevons paradox—a principle suggesting that enhanced efficiency does not diminish the demand for a resource but rather amplifies it, as the scope of work expands to accommodate the newfound capacity. As Bantock articulated regarding engineering talent in this era: “They’re suddenly a lot more productive, and there’s endless work for them to do.”