A European AI team is most elite at Series A
Track Europe's most-watched AI startups by funding stage and a clean arc appears: pedigree peaks at Series A, then dilutes as the team scales tenfold. It is a planning tool, not a warning.
By Laurence Sangarde-Brown · July 14, 2026
The Engineers of European AI
A European AI team is most elite at Series A
Team composition is not static. Track the most-watched startups by funding stage and the same arc appears every time: teams get less credential-dense as they get bigger.
Founders benchmark their team against companies at a completely different stage, then worry about a gap that is really just arithmetic. The arc is regular enough to plan around.
Peak pedigree, then dilution
At Series A the engineering team is at its most credential-dense: around 51% hold a top-100 degree and 21% a PhD. This is the small, hand-picked founding core, the phase where founders can be maximally selective. It is the most rarefied a team will ever be.
By Series B and into Series C+, the average team grows roughly tenfold, pedigree settles into the low thirties and PhD density more than halves. This is not decline. It is a team getting broader, because you cannot hire two hundred people who all clear a Series-A bar, and you would not want to.
The operator shift
Big-Tech alumni move the opposite way, rising from about 10% at Series A to 18% at Series C+. As the org grows, founders deliberately bring in people who have run larger functions before, trading raw research density for operational experience.
Benchmark against your stage. A Series-A lab and a Series-C company are different animals; do not hold them to the same yardstick.
Over-index on pedigree early. Selectivity is cheap when the team is small.
Bring in operators later. When execution is the constraint, experience running scale beats another research hire.
Composition follows a predictable arc with scale, and knowing the arc is a planning advantage.
The composition you can achieve at Series A is not the one you will sustain at Series C. That is normal, not failure.
Defend the pedigree that made you distinctive where it matters, and let the team broaden everywhere else.
Every figure here comes from The Engineers of European AI, our study of 27,444 engineers across 348 AI companies building in Europe.