Responsibilities Establish AI within engineering Further develop AI across the entire software stack with a strong focus on innovation, practical implementation, scalability and sustainable integration Orchestrate agent-based systems Design, build and manage AI agents and their interactions within complex system landscapes Shape use cases and architectures Identify meaningful application areas and develop scalable architectural approaches Move prototypes into production Convert ideas and PoCs into productive, stable solutions Optimize DevOps & workflows Apply AI to improve development processes, CI/CD, GitOps and operational workflows Design technically Develop and integrate modern AI solutions (LLMs, RAG systems, agentic architectures) Further develop our own framework Work with and expand an existing internal framework for AI-supported development and automation Ensure quality and compliance Take regulatory requirements, explainability/traceability, security and testing into account Requirements Strong architecture and engineering background Several years of experience in software architecture, complex system landscapes (DevOps) and modern development processes Experience in AI development Hands‑on experience building and deploying AI systems, especially LLMs and agent-based approaches Know‑how in agent orchestration Understanding of multi‑agent systems, workflows and their integration into existing systems Experience with modern DevOps practices Knowledge of CI/CD, GitOps and automated development processes Hands‑on mentality Ability to implement concepts independently and bring them into production Analytical and structured thinking Ability to evaluate technologies in terms of benefits, risks and scalability Strong communication skills Confident collaboration with technical and non‑technical stakeholders Experience in regulated environments (advantage) Understanding of requirements in financial or safety‑critical contexts Experience with Scrum is a plus #J-18808-Ljbffr
