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SignalFire data shows engineers now account for 55% of Tech Major new hires, defying predictions that AI would hollow out software roles across the sector.
- Engineering hiring fell just 11% from 2019 levels at Tech Majors, while total tech headcount fell 25% over the same period.
- AI/ML job postings surged 163% year over year in 2025, with global open positions topping 500,000 and median salaries above $138,000.
- Cisco job cuts of 4,000 roles and Intel layoffs totaling 24,000-plus reflect AI-driven workforce reallocation, not sector-wide retreat.
Lead
The data land squarely against the prevailing narrative. As more than 157,000 tech workers have lost their jobs in 2026 and tech layoffs stretch into a fourth consecutive year, new research shows that software and infrastructure engineers have proven the most durable occupational category in the sector's workforce. A June 2026 analysis by venture capital and talent analytics firm SignalFire, drawing on verified employment data across twelve companies it designates as Tech Majors—Alphabet (GOOGL), Meta (META), Apple (AAPL), Amazon (AMZN), Microsoft (MSFT), Netflix (NFLX), NVIDIA (NVDA), Tesla (TSLA), Uber (UBER), Airbnb (ABNB), Block (XYZ), and Stripe—finds that engineers now make up 55% of all new hires at those companies, a rise from 46% in 2019.
What the Data Show
Overall hiring at the Tech Majors has fallen 25% from 2019 levels, a period encompassing the post-pandemic correction, sustained high interest rates, and accelerating automation investment. Against that backdrop, engineering roles declined by just 11%—a gap that reflects structural preference rather than cyclical timing.
The composition shift reinforces the point. Operations, marketing, legal, and human resources functions bore a disproportionate share of tech layoffs since 2022, while engineering teams were cut more selectively and, in many cases, rebuilt around AI specializations. Each engineering manager at a Tech Major now oversees roughly twelve engineers, up from ten in 2019—a compression that reflects both leaner staffing and a sustained preference for senior, high-output talent.
AI and machine learning roles led all job categories in growth during 2025. Postings in AI, ML, and data science totaled 49,200 for the year, a 163% increase from 2024. Globally, more than 500,000 AI engineering positions remain open as of mid-2026, carrying a median annual salary of $138,000.AI as Cause and Cure
Across 267 publicly disclosed layoff events tracked through June 2026, 150—roughly 56%—explicitly cite AI, automation, or machine learning as a contributing factor, affecting an estimated 156,270 workers. The affected roles cluster in customer support, content moderation, data entry, quality assurance, and administrative functions where large language models and workflow-automation tools have demonstrably reduced labor requirements.
The pattern is a portfolio rebalancing, not a general contraction. Companies reducing headcount in automatable areas are simultaneously expanding in AI infrastructure, cloud security, and platform engineering. AI-related job postings have increased 340% since 2024, even as traditional software engineering postings declined 15% in the first two months of 2026 relative to the same period a year earlier. The net math favors engineers with AI-adjacent skills.
Intel and Cisco: Divergent Stories, Common Thread
Intel's (INTC) restructuring stands as the sector's most sweeping. Under CEO Lip-Bu Tan, Intel layoffs eliminated more than 24,000 positions through the end of 2025, followed by an additional 2,400 in January 2026, reducing global headcount from roughly 125,000 toward a target of approximately 75,000. A fresh wave of Intel layoffs is scheduled to take effect July 15, 2026, concentrated in Oregon manufacturing campuses, with approximately 2,400 additional roles affected. The cuts are designed to reduce Intel's operating expenses by an additional $1 billion in fiscal 2026 as the company reconfigures its business around AI chip design and foundry services. Cisco's (CSCO) recent moves illustrate a different dynamic. On May 13, 2026, CEO Chuck Robbins announced a Cisco layoff of fewer than 4,000 employees—approximately 5% of the company's 80,000-person global workforce—framing the Cisco job cuts explicitly as a redeployment of capital toward silicon, optics, security, and AI. The announcement arrived alongside Cisco's fiscal Q3 2026 results showing record quarterly revenue of $15.8 billion, up 12% year over year. Cisco shares surged 15% on the day.Cisco booked $1.9 billion in AI infrastructure orders from hyperscalers in Q3 2026 alone, lifting the fiscal year-to-date total to $5.3 billion. The company raised its full-year AI infrastructure order guidance to approximately $9 billion—4.5 times the fiscal 2025 total. The Cisco job cuts followed earlier rounds in 2024 and 2025 that together removed more than 15,000 positions. In each instance, Robbins cited AI-led demand as both the rationale for the reductions and the destination for freed capital.
Entry Level: A Persistent Pressure Point
Not every engineer is equally shielded. New graduate and entry-level hiring at the Tech Majors has fallen approximately 65% from 2019 levels; at early-stage startups, the decline reaches 76%. Graduates from top-20 U.S. computer science programs in 2025 are 45% less likely to secure a role at a Tech Major than their counterparts from a few years prior. Competition for junior positions has intensified as candidate supply per posting climbed and experience bars on open roles have tightened. Developers who combine AI-tool proficiency with systems design expertise are securing roles 2.3 times faster than those without those attributes.
Outlook
Six months of 2026 data support a durable occupational split: engineering functions are absorbing the AI era better than any other large category in technology, even as total tech layoffs continue at a rate approaching 900 workers per day industry-wide. Intel layoffs and Cisco job cuts illustrate how prominent companies are simultaneously reducing headcount in legacy functions and expanding AI-oriented engineering teams—a reallocation that the hiring data increasingly characterize as structural. Entry-level engineers face the sharpest constraints, but mid-level and senior talent with AI-adjacent skills remain in sustained demand. The premium attached to AI engineering is hardening into a permanent feature of the labor market rather than a transient spike.
