The AI pay premium does grow with seniority. Levels.fyi found that AI-focused software engineers earned 6.2% more than non-AI engineers at entry level in 2025, and 18.7% more at staff level. The premium for the newest hires has shrunk, while the premium for the most experienced has widened.
Anyone deciding when to specialize should read the pattern carefully. The rest of this article shows what the primary data says at each level, where it comes from, and where it stops being reliable.
Does the AI pay premium grow with seniority?
The AI pay premium grows with seniority, and it climbs at every step of the ladder. Levels.fyi compared AI-focused software engineers with their non-AI peers at the same level, using US compensation submissions. The gap was 6.2% at entry level, 11.9% for mid-level engineers, 14.2% for senior engineers and 18.7% for staff engineers in 2025.
The Levels.fyi data is American, so the percentages describe the US market, not Europe. No European dataset publishes the same split by level, which is worth knowing before treating 18.7% as a European figure. The direction is the useful part, and the wider evidence agrees with it.
Is the entry-level AI premium shrinking?
The entry-level AI premium is shrinking, and it fell faster than any other level. Levels.fyi measured 10.74% for entry-level AI engineers in 2024 and 6.2% in 2025. Over the same year the staff-level premium rose from 15.8% to 18.7%, while the senior figure barely moved (14.3% to 14.2%).
| Level | 2024 premium | 2025 premium |
|---|---|---|
| Entry level | 10.74% | 6.2% |
| Engineer | 11.6% | 11.9% |
| Senior engineer | 14.3% | 14.2% |
| Staff engineer | 15.8% | 18.7% |
Source: Levels.fyi, US data.
One plausible reading is supply. More graduates now arrive with machine learning coursework, so the skill is less scarce at the bottom of the ladder. Experienced engineers who have shipped models to production remain hard to find. That is an interpretation, not something Levels.fyi states.
Why do employers pay more for experienced AI talent?
Employers pay more for experienced AI talent because AI work has moved toward tasks that need judgment, not only technique. PwC’s 2026 Global AI Jobs Barometer, which analyzed more than a billion job advertisements across 27 countries and territories, found that AI-exposed entry-level roles are seven times more likely to ask for traditionally senior skills such as judgment and leadership.
The same report puts the average wage premium for AI skills at 62% globally. That figure compares workers with and without AI skills across all occupations, so it is not comparable with the Levels.fyi engineer-to-engineer gap. Both can be true at once. A broad premium for the skill sits alongside a narrower premium within one profession.
How large is the AI premium in absolute terms?
The AI premium in absolute terms depends on the market, and the gap between countries dwarfs the gap between levels. Stack Overflow’s 2025 Developer Survey reports a global median salary of $89,427 for AI and ML engineers, against $82,910 for data scientists. In the US the AI and ML engineer median is $189,500.
Lightcast analyzed more than 1.3 billion job postings and found that postings with AI skills offer 28% higher salaries, nearly $18,000 more per year. Half of those postings (51%) sit outside IT and computer science, so the premium is not limited to engineers.
| Source | What it measures | Finding |
|---|---|---|
| Levels.fyi | AI vs non-AI engineers, same level, US | 6.2% (entry) to 18.7% (staff) |
| PwC 2026 | Wage premium for AI skills, 27 countries | 62% on average |
| Lightcast | Salary premium in AI-skill postings | 28%, nearly $18,000 a year |
| Stack Overflow 2025 | Median pay, AI and ML engineers | $89,427 global, $189,500 US |
Can you trust the AI premium figures for Europe?
The AI premium figures can only be trusted for Europe as a direction, not as a number, because none of the datasets above was built around European pay. Levels.fyi reports US submissions. PwC and Lightcast measure advertised wages in dozens of countries at once, and Stack Overflow relies on self-reported salaries that vary heavily by country and currency.
Each source also defines “AI” differently. Levels.fyi labels engineers as AI-focused by their role and team. PwC and Lightcast count postings that name AI skills. A marketing manager who lists prompt engineering counts in the second group and not the first. Two figures that look contradictory, 18.7% and 62%, are often measuring different populations against different baselines.
For a job seeker, the safe conclusion is modest. Seniority strengthens the premium in every dataset that splits by level, and no dataset shows the premium disappearing with experience. The exact European percentage is unknown, so compare live offers against a peer range instead of a headline.
How should you use the seniority premium when negotiating?
Using the seniority premium in a negotiation works best when it supports a specific claim about your own scope. Citing “an 18.7% premium” to a European employer invites the reply that the figure is American. Pointing to production ownership, a model in use by customers or a team you led gives the premium something concrete to attach to.
Employers respond to evidence of the work the premium pays for. Benchmarks help you frame the range, but a stated scope decides where in that range an offer lands.
Should you specialize in AI early or later in your career?
Whether to specialize in AI early or later depends on what the data rewards, and it rewards depth over a label. An entry-level premium of 6.2% is real but small. The staff-level premium of 18.7% goes to people with years of applied work behind them.
In our analysis of 500+ live European AI roles across 90 companies, 37% carry a senior, staff, principal or lead title, in line with the external finding that employers place the most weight on experienced AI talent.
A practical reading for a European candidate follows from that. Early in a career, build a strong engineering base and ship something real with machine learning. Mid-career, move toward production ownership, since that is where the levels data shows the premium widening. Treat every percentage above as a US or global benchmark and check it against European offers before negotiating.
To see what experienced roles look like now, browse remote AI engineer jobs and remote machine learning jobs. Candidates aiming at the research end can start with remote AI research jobs.