Countries Hiring for AI — Where the Jobs Actually Are

Vecta continuously indexes tech job postings from countries hiring for AI, classifies them using machine learning, and extracts structured data: location, salary, remote policy, experience level, tech stack, and AI categorisation. This analysis covers 13,506 active postings across 20+ countries.

Every role is classified as AI or non-AI based on its full job description — not just the title. A “Software Engineer” building ML pipelines counts as AI. A “Data Scientist” doing Excel dashboards doesn't.

If you picked a random tech job posting in San Francisco, there's a nearly three-in-four chance it involves AI. At 73.5%, San Francisco's AI concentration is more than double the global average of 34.5%.

Singapore is the only other city that comes close, at 65.6%. After that, there's a sharp drop. London sits at 51.3%. Most major cities are in the 30-45% range. Chennai, one of India's largest tech hubs, is just 16.2%.

The pattern is clear: AI hiring isn't distributed evenly. It clusters in a handful of cities — and the gap between the top tier and everyone else is massive.

At the country level, the split among countries hiring for AI varies just as much. The United States has the highest AI concentration (44.5% of its tech postings are AI), followed by Ireland at 42.3% — likely driven by the Dublin cluster of Big Tech European HQs. The United Kingdom sits at 39.5%.

India and France, despite large tech markets, have below-average AI concentrations at 29.1% and 28.4%. Poland is the lowest among major markets at just 17.3% AI.

Across all 13,506 postings, 42% of remote roles are AI positions — compared to just 29% of onsite roles. AI companies are significantly more willing to hire remotely than the broader tech market.

But remote policy varies enormously by geography. The UK is a hybrid-first market — 66% of UK postings are hybrid, compared to 46% in the US. India is the opposite: a majority-onsite market where 63% of roles require full office attendance and just 5% are fully remote.

And even “hybrid” doesn't mean the same thing everywhere. Hybrid roles in the US average 3.0 days in office. In France it's 2.5 days. In Italy, just 2.2. If a candidate in Rome and one in New York both accept “hybrid” roles, their week looks quite different.

Comparing AI salaries across countries hiring for AI sounds straightforward. It's not. The fundamental problem: salary transparency varies so wildly by country that any cross-border comparison is built on an uneven foundation.

The US is a transparency outlier: 72% of postings include salary data, partly driven by state-level pay transparency laws in Colorado, New York, California, and Washington. Canada follows at 57%.

Europe is opaque. The UK, despite being the second-largest market in our dataset, publishes salary on just 18% of postings. France is 15%. Germany, 11%.

India — the third-largest market by volume — publishes salary on effectively less than 1% of postings (6 out of 1,490). This means any India salary benchmark you see elsewhere is either survey-based, self-reported, or fabricated.

Not every country hiring for AI is looking for the same rung of the career ladder. France is a standout: 24% of its AI roles are junior-level. In the US, that figure is just 3%. In the UK, it's 5%.

This matters if you're thinking about where to start an AI career. France's hiring profile is building a talent pipeline. The US and UK are importing experienced practitioners — 59% and 66% of AI roles are senior, respectively. India's profile leans senior but has a notable principal/staff cluster (10%), likely reflecting large enterprise centres of excellence.

For junior AI engineers: France, in particular Paris, is where the entry points are. For senior engineers, the US and UK remain the deepest markets.

Python is universal — the top AI technology in every country we analysed. Beyond that, the stack diverges significantly across countries hiring for AI roles.

LangChain appears in the top 5 AI technologies in the US (349 mentions) but doesn't crack the top 10 in the UK, France, or India. This suggests that the agentic/RAG tooling wave is still heavily US-centric in hiring terms.

PyTorch, on the other hand, is the #3 technology in the UK (323 mentions) and prominent in France (75 mentions) but further down in the US. The UK and French AI markets lean more towards research-heavy ML engineering — training models, not just calling APIs.

India's stack is notable for BigQuery ranking as high as Docker (222 mentions each), reflecting the enterprise data engineering orientation of India's AI hubs. France leans into PyTorch and PostgreSQL — a stack that suggests research and startup environments more than big-cloud enterprise deployments.

The landscape of countries hiring for AI isn't a smooth gradient. It's clustered, uneven, and shaped by local forces — regulation (salary transparency laws), culture (remote work norms), industry structure (research vs enterprise), and talent pipeline (junior vs senior).

This analysis covers 13,506 active job postings from Vecta's database as of February 2026. Every posting is classified as AI or non-AI using Vecta's AI classifier, which reads the full job description — not just the title or keywords.

Location data is extracted and normalised to city and country level. Of 13,506 postings, 12,158 (90%) have country data and 10,657 (79%) have city data. Postings without location data are excluded from geographic breakdowns but included in overall totals.

Salary data is included only where the original posting listed a salary range. We do not estimate or infer salaries. Cross-currency comparisons are noted but not normalised — a £125K London salary and a $229K San Francisco salary are reported in their listed currencies.