March 2026 Jobs Report

Tech job postings increased 5% month-over-month in February, continuing the recovery that began in January. Unlike January’s rebound from typical year-end hiring slowdowns, February’s growth reflects more deliberate forward momentum as organizations move from planning into active hiring. The market also turned positive on a year-over-year basis for the first time in recent months, with postings up 6% compared to February 2025, a meaningful signal that the broader market is stabilizing. 

AI skills requirements continued their upward trajectory in February, reaching 61% of U.S. tech job postings, up from 58% in January. Year-over-year, AI skill requirements have increased 136% from February 2025 — reflecting how deeply AI capabilities have been integrated into role expectations across the technology sector as companies move production-scale AI deployments from early experimentation into ongoing operations. 

Regional hiring patterns show continued recovery

At the state level, February brought broad-based improvement across most major tech markets. The top five states by hiring volume all posted month-over-month growth: New York (+25%), New Jersey (+23%), Massachusetts (+7%), Texas (+7%), and California (+5%). Illinois (-1%), Virginia (-1%), and Maryland (-4%) were the only states to post month-over-month declines. 

Year-over-year, the state-level picture improved considerably. New York (+17%), Massachusetts (+13%), New Jersey (+10%), California (+6%), and Maryland (+5%) all posted positive growth. Florida (-8%) and Virginia (-12%) were the only states with year-over-year declines, reflecting reduced federal contract spending in the D.C.-Virginia corridor and broader workforce rationalization in Florida’s tech market. 

At the metro level, NYC led February growth with a 33% month-over-month increase, followed by Austin (+17%), San Jose (+14%), and Los Angeles (+9%). Boston and Washington D.C. also posted positive gains. The one notable exception was San Francisco-Oakland-Fremont, which declined 14% month-over-month. 

San Francisco’s pullback aligns with a wave of high-profile layoff announcements in early 2026. Block, Meta, Autodesk, and others filed California WARN notices in January and February, with Bay Area reductions affecting hundreds of positions across engineering, product, and corporate functions.  

Year-over-year metro performance told a more positive story. New York (+22%), San Jose (+15%), Austin (+14%), and Boston (+13%) all posted double-digit growth. New York’s performance reflects the maturation of its tech sector as a cross-industry capability layer embedded in finance, healthcare, and media. Austin continues to benefit from cost advantages, a growing talent pipeline, and an established base of major employers including Dell, Apple, and IBM. Boston’s strength is tied to its biotech and enterprise software ecosystem, anchored by the ongoing collaboration between industry and its network of research universities. 

February hiring patterns reflected strong demand for roles spanning security, AI infrastructure, enterprise systems, and engineering operations. Month-over-month job title growth above 150% included Cyber Threat Analysts, Machine Learning Operations Engineers, Analytics Developers, Substation Engineers, Appian Developers, Solutions Consultants, IT Field Support Technicians, SAP PP Consultants, and Back End Engineers. 

The skills landscape tells a coherent story across two themes. The first is enterprise modernization: ABAP (+68%), Lean Six Sigma (+66%), PeopleSoft (+44%), and the strong showing of SAP PP Consultants in the job titles all point to active ERP migration and business process transformation work, particularly in manufacturing, insurance, and healthcare. The second is AI production infrastructure: Real-Time Data (+47%), Postman (+44%), Endpoint Detection and Response (+40%), JSON (+38%), and Rust (+38%) reflect the API, data pipeline, and security work required to run AI systems at scale. Governance, Risk Management and Compliance (+46%) bridges both themes, as organizations deploying AI into enterprise environments face new requirements around data governance and model risk.