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DevOps Engineer – Cloud Native AI

Pubblicato il 13-10-2026 - AI Venture Builder in Roma

- Employment Type: Full-Time, preferably Freelance
- Department: Engineering / AI Infrastructure
- Language Requirement: Italian & English

The Opportunity: Join a Rocket Ship

AIVB isn't just a startup; we are a high-velocity scaleup redefining how AI solutions reach the market.
- Hyper-Growth: 300% YoY growth, jumping from zero to £1.4M in our first full year.
- Proven Pedigree: Founded by the pioneers behind Deep Learning Italia, the gold standard for AI education in Italy.
- Global Ambition: Backed by £4.5M in seed funding, we are preparing for a major US-led Series A in Q4 2026 to dominate international markets.

We are building the "Operating System" for AI ventures. We don't just build products; we build companies.

About AIVB

Founded in 2024 by Marco Tognoni and Matteo Testi, AIVB is an AI Venture Builder designed to scale innovation at speed. Our team of 40 is anchored by an elite engineering core, primarily AI PhDs, who transform complex research into vertical‑specific powerhouses.





We operate through a Centralized Powerhouse that develops strategic blueprints for specialized spinoffs in high‑impact sectors such as Fashion, Real Estate, and CyberDefense. We are "International by Design", English is our language, and global scale is our target.

Why this role matters

We are building cutting‑edge AI solutions within the boundaries of the Italian National Cloud Strategy. You won't just be clicking buttons in AWS; you will be architecting compliant, self‑hosted AI platforms on sovereign infrastructure. This is a role for an engineer who understands how to build cloud‑native reliability without relying on public hyperscalers.

Role Summary

As a DevOps Engineer for Sovereign AI, you will design and maintain the infrastructure that powers our AI/ML workloads on Italian National Cloud providers (e.g., SeeWeb, Netalia, Aruba). Your focus will be on self‑managed Kubernetes, strict Data Sovereignty, and implementing open‑source MLOps toolchains that function indep

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