Engineering Jobs Prove Unexpectedly Resilient Despite AI Wave

Tech companies announced 97,006 job cuts in May 2026 — the highest single month since 2020 — and AI was the most-cited reason for those layoffs. Yet behind that headline sits a surprising trend: engineering jobs are among the most resilient positions in the market. According to SignalFire's 2026 State of Talent Report, which tracked millions of employees across more than 80 million companies, software engineers have actually increased their share of new hires at major tech firms. At the twelve largest tech companies tracked — including Alphabet, Meta, Apple, Amazon, Microsoft, and Netflix — engineers now make up 55 percent of all new hires, up from 46 percent in 2019. For early-stage startups, the picture is even stronger: hiring of engineers in 2025 was up 7 percent compared to 2019 levels.

The broader context matters. Overall tech hiring has stalled at just 75 percent of its pre-pandemic baseline, and at the large tech companies, hiring is running 25 percent below 2019 levels on a trailing twelve-month basis. This is the lowest point since the major crash of 2023. Entry-level hiring has been hit particularly hard, down roughly 65 percent at major tech firms and down approximately 76 percent at early-stage startups compared to 2019. Yet within that contracting pie, engineering roles have managed to shrink far less than other functions. Engineering hiring is down only 11 percent compared to 2019 — a modest decline in an industry that has cut deeply in other areas.

The data suggests that while AI has triggered significant workforce reductions in certain roles — and will likely continue to do so — companies are not abandoning their engineering talent. Instead, they appear to be doubling down on it. Asher Bantock, head of research at SignalFire, noted the disconnect between the fear narrative and ground reality: "What we're seeing on the ground is a little inconsistent with that" — referring to predictions that AI would replace software engineers. Jensen Huang, CEO of NVIDIA, captured the same observation differently: "Software engineers are busier than ever." The reality may be that AI is not so much replacing engineers as it is changing what they do and creating new kinds of engineering roles — including AI engineering positions — that require the same foundational technical skills.

One likely explanation is that AI development and deployment require sophisticated technical talent. Companies racing to integrate AI into their products and operations need engineers who understand systems architecture, data pipelines, infrastructure, and the intricate work of actually building and shipping AI applications. Those skills are not easily replaced by the technology itself. The market for experienced engineers remains tight, and the companies that can retain and attract engineering talent are better positioned to capitalize on the AI wave. Startups, too, have been selective: they are hiring fewer people overall, but when they do hire, they are prioritizing engineers over other functions. This suggests that engineering is seen as a core, defensible competency in an uncertain market.

The tech sector's experience may not mirror every industry. Finance, customer service, and administrative roles have faced more explicit automation pressure from AI, and some sectors may see different outcomes. However, the engineering data provides a counterpoint to the most dire job-displacement predictions made in 2025 and early 2026. While companies are clearly using AI to do more with fewer people in some roles, they are not abandoning the technical talent needed to build and operate AI systems themselves. The takeaway is more nuanced than either uncritical optimism or panic: some jobs are declining, but the jobs most essential to creating and deploying the new technology are holding up — even growing as a proportion of hiring.

This story underscores a critical lesson for business leaders: decisions about hiring, retention, and skill investment require accurate, complete data. Companies that had fragmented people data spread across multiple HR systems, payroll platforms, and disconnected spreadsheets would struggle to see patterns like the one SignalFire uncovered. They might not know whether they are actually shifting investment toward engineering or inadvertently letting technical talent atrophy. As businesses move into an AI-enabled future, the pressure to make smarter, faster decisions about workforce strategy will only increase. A unified data foundation — one that brings together hiring records, skills inventories, retention metrics, and market trends into a single source of truth — becomes essential. That foundation allows leaders to ask better questions: Which roles are we actually investing in? Are we retaining the talent we need for our AI transformation? How do our hiring patterns compare to the market? Without integrated data, those questions are nearly impossible to answer confidently. The companies capturing and acting on this kind of insight first will have an edge in competing for the engineering talent that clearly remains in high demand.