AI ARCHITECT
Pubblicato il 12-08-2026 - Allianz in Roma
The Global P&C; team is an Allianz SE department established in 2011, building on the Center of Competence initiative launched in 2005. Its mission is to support all Allianz P&C; Entities in achieving technical excellence by leveraging Allianz capabilities across data management, tariff development, portfolio analysis, and monitoring. The Global P&C; Pricing team defines standards, best practices, and guidelines — and supports their implementation — across the full pricing lifecycle. The team is currently embedding Artificial Intelligence and Generative AI into insurance pricing processes through agentic architectures, working at the intersection of actuarial science, data engineering, and cutting-edge AI.KEY RESPONSIBILITIESDesign and develop end-to-end AI architectures for insurance pricing, spanning retrieval and knowledge systems, agentic workflows, and production deployment.Lead the integration of AI and ML models (GLMs, LightGBM), rating engines, and portfolio data into agentic architectures,
enabling pricing analysts to interact with the pricing stack in natural language.Build and maintain LLM-powered tools that accelerate tariff analysis, pricing code generation, what-if simulations, and regulatory documentation.Rapidly prototype AI solutions and present them in workshops and advisory sessions with senior stakeholders, translating complex technical concepts into actionable insights.Collaborate closely with actuaries, data scientists, and AI Transformation Architects to ensure AI solutions are scalable, robust, and aligned with business objectives.Contribute to the definition of AI architecture standards and best practices within the Global P&C; Pricing team.EDUCATION / EXPERIENCE / SKILLSBachelor's or Master's degree in a quantitative field (e.g., Mathematics, Physics, Computer Engineering, Data Engineering, or a related discipline).At least 3–5 years of practical experience in designing and deploying end-to-end GenAI solutions, gained in a professional context.