Quantum Application Engineer
Pubblicato il 30-08-2026 - Classiq in Napoli
Classiq is a quantum computing software company. We build the platform that enterprise teams and government organizations use to develop, optimize, and deploy quantum software across any quantum hardware. We're a growth-stage B2B technology company with 100+ patents and a global footprint across North America, Europe, APAC, and Israel.
Classiq is expanding its presence in Italy by building a new quantum computing center, and we're looking for our first on-site hire to lead its day-to-day operations. You'll be the local technical and operational face of the platform for the center's users, running onboarding, training, and support.
This is a hybrid technical customer support profile, including technical presales, training, customer support, implementation, and research. You'll join as an early, founding member of a new site, with real autonomy to shape how it runs.
What you'll do
Serve as the on-the-ground technical point of contact for the center's platform users.
Deliver hands-on onboarding and training on the Classiq platform for researchers, engineers, and end users in Italian.
Provide first-line technical support and troubleshooting for platform users.
Implement quantum applications hand in hand with the local enterprise customers.
Own day-to-day center operations: user and license management, hardware/resource access allocation, etc.
Build strong working relationships with the partner's team - surfacing risks and requirements, and feeding field insights back to Classiq.
Represent the center for visiting customers and partners (demos, walkthroughs) - customer-facing.
As an early hire, help stand up center readiness -space, equipment, and workflows as the team grows.
Who you are
Advanced degree (MSc or PhD) in Physics, Computer Science, or Engineering, with a strong academic or practical focus on quantum computing or quantum information.
Prior experience in technical customer support, training delivery, or platform/site operations.
Comfortable learning and explai