AI Engineer
Pubblicato il 08-09-2026 - Brightstar Italia in Roma
Location: Roma, IT, 00154
Requisition ID: 19460
Brightstar is an innovative, forward-thinking global leader in lottery that builds on our renowned expertise in delivering secure technology and producing reliable, comprehensive solutions for our customers. As a premier pure play global lottery company, our best-in-class lottery operations, retail and digital solutions, and award-winning lottery games enable our customers to achieve their goals, fulfill player needs and distribute meaningful benefits to communities. We have a longstanding commitment to Responsible Gaming (RG) that is engrained within our core business and the products we offer to customers and players worldwide. Brightstar has a well-established local presence and is a trusted partner to governments and regulators around the world, creating value by adhering to the highest standards of service, integrity, and responsibility. Brightstar has approximately 6,000 employees. For more information, please visit www.brightstarlottery.com.
Role Overview
We develop and operate a highly data-intensive platform offering analytics,
machine learning and agentic AI on cloud environments. As part of continued investment, we are building a cutting-edge AI-native decision-system.
As an Agentic AI Developer, you will be responsible for designing and developing advanced agentic AI solutions capable of autonomous planning, reasoning, and task execution. Developing and integrating Retrieval-Augmented Generation (RAG) pipelines to enhance agents' reasoning capabilities with external knowledge sources, and multi‑agent communication protocols to enable seamless collaboration and coordination among agents. Collaboration will be key, as you work cross‑functionally with Data Scientists, ML Engineers, and Product Teams to deliver robust, end‑to‑end AI solutions.
You will work at the intersection of cutting‑edge AI, Data Science and modern software engineering, implementing multi‑agent frameworks and orchestrating interaction