Key Takeaways

  • SignalFire data shows engineering hiring fell far less than other roles in 2025.
  • Tech Majors including Alphabet, Meta, Apple, Amazon, Microsoft, Netflix, Nvidia, Tesla, Uber, Airbnb, Block, and Stripe increased the share of engineers in new hires.
  • Industry research points to AI reshaping rather than replacing engineering work.

Many executives and analysts have argued through 2025 and into 2026 that AI would rapidly automate white-collar jobs. In May, tech layoffs hit their highest single-month total in years, and AI was the most cited justification according to outplacement firm Challenger, Gray & Christmas. Yet career tracking data indicates a different trend.

Instead of collapsing, engineering roles appear to be holding up better than most. SignalFire reviewed millions of employee records across more than 80 million companies and found that engineering was the most resilient job function in 2025. Total hiring across large tech companies declined 25% compared to 2019 levels, but engineering roles saw only an 11% drop.

On one side, companies have leaned into the idea that AI lets a single engineer do the work of several, which seemed to help justify downsizing. On the other, the head of research at SignalFire stated the firm's real-time hiring data does not support that narrative. Hiring, not layoffs, tends to reveal what organizations truly need in the moment.

The concentration of engineering hires at the biggest tech firms actually increased. Engineers represented 55% of all new hires in 2025 across the 12 companies SignalFire categorizes as Tech Majors, which include Alphabet, Meta, Apple, Amazon, Microsoft, Netflix, Nvidia, Tesla, Uber, Airbnb, Block, and Stripe. Back in 2019, engineers represented only 46% of those companies' new hires. Early-stage startups also leaned further into engineering talent, bringing in 7% more engineers in 2025 than they did in 2019.

If AI tools were truly substituting for engineering labor at scale, the head of research suggested that engineering would be the first function to drop sharply in a downturn. Instead, engineering headcount is expanding relative to other job groups.

This pattern fits broader research. A 2024 analysis from the World Economic Forum found that architecture and engineering roles ranked among the least likely to face full automation. The report noted that AI typically augments engineering work, and global demand for these roles is projected to grow through 2030. That view aligns with McKinsey's 2023 workforce scenarios as well. McKinsey estimated that only about 12% of jobs face direct substitution by AI. In contrast, 50% to 55% are more likely to be reshaped with new task mixes, shifting engineers toward system-level design and complex problem solving rather than eliminating their roles entirely.

The Stack Overflow Developer Survey from 2024 found that more than 70% of professional developers already use AI coding tools. Those tools have not reduced the need for engineers. In fact, the same survey noted persistent demand for experienced developers, with acute shortages in areas like cloud engineering, data engineering, and AI or machine learning engineering.

A different kind of evidence comes from companies building AI systems. Anthropic's CEO warned last year that AI could eliminate half of entry-level white-collar jobs and push unemployment as high as 20% within five years. Yet Anthropic's head of economics told TechCrunch in March that he had not observed significant AI-driven workforce effects. He pointed out that there is no larger difference in unemployment rates between workers using Claude for core tasks and workers in roles requiring physical interaction or dexterity.

Nvidia's CEO added another perspective when speaking at the Stanford Graduate School of Business in April, rejecting the idea that AI will replace engineers. All engineers at Nvidia now use agentic AI, he noted, and rather than decreasing the need for engineers, the tools have made them busier than ever. Agents can write code quickly, but they still depend on engineers to originate ideas and define direction.

Some frameworks also slow down the pace of automation. Safety-critical engineering, like automotive systems governed by ISO 26262 or industrial control governed by IEC 61508, typically requires extensive human judgment and formal verification. Even as AI becomes more involved in design or simulation, these frameworks limit how far automation can go without human oversight.

Taken together, these signals help explain why hiring patterns are not collapsing. Efficiency improvements create more demand in many cases, not less. The description of engineers generating the next idea once an agent writes code almost instantly fits what economists call the Jevons paradox. When a resource becomes more efficient, usage can expand.

While layoffs tied to AI are occurring, engineering roles seem to follow a different trajectory. Productivity jumps have opened more work, and startups as well as Tech Majors continue to build around engineering as a core capability. For now, engineering is being reshaped and potentially amplified rather than erased by AI automation.