Skills are extracted from job listings using AI-powered analysis. The chart below shows the most frequently requested skills across all tracked companies, with the full breakdown in the table.
The skills landscape in tech hiring tells a clear story: companies are investing heavily in AI and machine learning capabilities while maintaining strong demand for foundational engineering skills. Python, cloud platforms, and distributed systems remain table stakes for most technical roles, but the fastest-growing requirements center on large language models, retrieval-augmented generation, and ML infrastructure.
What stands out in our data is the breadth of AI adoption. It is no longer confined to dedicated ML teams — skills like prompt engineering and vector databases now appear in backend, platform, and even product roles. Meanwhile, traditional skills like SQL and Java hold steady, suggesting companies are augmenting rather than replacing their existing tech stacks.
The percentage column in the table below shows how often each skill appears across all listings, giving a sense of which capabilities are broadly valued versus niche specializations.
The most common skill pairings across all job listings. The overlap percentage shows how often the pair appears relative to the less-common skill's total listings — a higher number means a tighter bond.
| Skill A | Skill B | Co-appearances | Overlap |
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Skill concentration by role category. Brighter cells indicate a higher share of that skill within the role. Read across a row to see where a skill is most valued.
| Category | Mentions | Share |
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| Skill | Category | Listings | % of Total |
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