Claims Solution Designer_2059
Pubblicato il 03-10-2026 - Allianz in Milano
About the jobJoin Allianz as a Solution Designer within our dynamic IT Claims team, which is responsible for the evolution and management of IT systems supporting claims processing. Our team plays a crucial role in continuously enhancing system functionalities to meet new business needs, managing systems in production, and defining and implementing the technological roadmap for platform evolution — including the introduction of Generative AI and Agentic AI solutions to transform both the claims experience for our users and the efficiency of our IT operations. The IT Claims platform is based on Java and Mainframe technologies, composed of both components deployed in the cloud and on-premises. We are on a trajectory to progressively transition from Mainframe to Java technology, complete the migration to cloud solutions, and embed intelligent, AI-driven capabilities into our platform.
In this context, we are seeking a Solution Designer with proven experience in shaping the adoption of emerging AI technologies,
implementing transformation projects and maintaining/evolving software solutions. You will contribute to the definition and execution of steps to evolve the platform towards our target architecture — where GenAI agents play an active role in claims handling and IT automation.
What you doPlay a major role in the ideation, design, and architectural definition of Agentic GenAI solutions for the Claims domain — covering both user-facing applications (e.g. intelligent claims intake, automated triage, virtual assistants for claimants and adjusters) and IT-side automation (e.g. agentic workflows for monitoring, incident management, and development productivity).Translate business and IT needs into GenAI solution blueprints, defining agent architectures, orchestration patterns, integration with LLM platforms, and guardrails for responsible and compliant AI use within Allianz's regulatory framework.
Extend existing solutions to enhance scalability, robustness, and securit