Tech hiring is rebounding for senior engineers, but interview standards have risen sharply, especially in AI roles, making interviews harder and more selective across big tech and startups.
The market has shifted from a frenzy of 2020-2022 to a selective recovery where senior engineers can still command multiple offers, but the bar for interview performance has moved up roughly one standard deviation. Interviews at big tech still follow the same formats, yet candidates now face harder DSA problems, stricter implementation expectations, and system-design questions that demand modern distributed-systems knowledge such as geohashing or exactly-once semantics.
Specialists in AI infrastructure, MLOps and generative AI are seeing a surge of high-compensation openings, while engineers focused on core backend, frontend or mobile roles face fewer opportunities and longer search cycles. New grads and mid-career engineers report dramatically longer loops-sometimes double-digit interview rounds-before receiving an offer, reflecting tighter hiring budgets and a higher emphasis on transferable skill sets.
For technical leaders, the takeaway is clear: hiring strategies must adapt to a market that rewards deep, high-impact specialization and expects managers to be hands-on with modern tooling. Coaching teams to broaden skill coverage, investing in AI-related upskilling, and tightening interview preparation around full-stack implementation details can improve hiring outcomes in this more demanding environment.
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