AI Operations Intern
Pubblicato il 30-08-2026 - Graduate Ventures in Italia
Space assets and services are not fully monetized. At Revolv Space, we are solving the problem of low duty cycles by developing and manufacturing the next generation of critical subsystems enabling continuous spacecraft operations and therefore full monetization of space assets.
We start with tackling the power limitations of small satellites by providing best-in-class products for small satellites: Solar Array Drive Assemblies, solar arrays and deployment mechanisms.
To achieve this mission, we are on the lookout for an AI Operations Intern who will act as our cross-departmental automation champion, transforming manual tasks into streamlined, AI-driven workflows. The ideal candidate will combine a sharp logical mindset with strong communication skills to help teams across Operations, Engineering, Procurement, HR, and Finance unlock their full potential through modern productivity tools.
TYPE: Full-time curricular internship
DURATION: 3-6 months
REMUNERATION: 600 EUR per month
LOCATION: Turin, Italy
START MONTH: September/October 2026
Responsibilities
Collaborate with various departments (Operations, Engineering, Finance, Procurement, HR, Sales) to identify repetitive, manual tasks eligible for automation
Design, build, and deploy automated workflows using low-code/no-code platforms to connect our daily tools
Support the integration of modern AI tools into daily business operations.
Write clear, simple guides for internal teams on how to use the new automated tools, and conduct short walkthrough sessions.
Continuously monitor existing automations, troubleshoot errors, and propose data-driven upgrades
Requirements
You must be currently enrolled in a Bachelor's or Master's program (e.g., Management Engineering, Business Administration, Computer Science, Data Science, or a related field) that allows for a curricular internship with university agreement
A strong passion for Generative AI (LLMs, prompt engineering) and modern productivity tools.
Basic familiar