Your area of work:

Within the CTO division at Deutsche Börse Group, we operate and develop the group-wide IT infrastructure - spanning networks, data centers, cloud environments, Group Data & Advanced Analytics, and our AI-driven Software Development Lifecycle (SDLC) platform. As Senior AI Engineer and Applied AI Engineer Lead, you will sit at the heart of our agentic automation pillar, driving the architecture and evolution of Agent Chain: an event-driven platform that automates the software development workflow from business idea to deployable code, serving a community of 1,400+ developers. This is a high-impact role that directly shapes Deutsche Börse Group's strategic technology direction in a regulated financial market infrastructure environment.

Your responsibilities:

• Architect and continuously evolve the end-to-end prompting framework and skills-based agent design, ensuring consistent, high-fidelity outputs across Refinement, Decision, and Coding Agents
• Design, build, and optimise multi-agent orchestration workflows using LangGraph, implementing agentic Retrieval-Augmented Generation (RAG) with iterative retrieval and Model Context Protocol (MCP) integration
• Engineer and fine-tune complex prompt chains for Claude Opus/Sonnet and other foundation models, systematically measuring accuracy, reliability, and compliance with EU AI Act and DORA requirements
• Develop and maintain Python-based AI services that bridge legacy systems (Jira On-Premise, 25,000+ GitHub repositories) with the target GitHub EU Cloud platform
• Mentor and technically lead AI engineers across the Agent Chain team, conducting code reviews, establishing prompt engineering best practices, and raising the overall engineering bar
• Collaborate with DevSecOps, Platform, and Architecture teams to ensure all agent actions are versioned, logged, and deployable through Kubernetes-based CI/CD pipelines on GCP

Your profile:

• Master's degree or higher in Computer Science, Artificial Intelligence, or a related field, combined with 5+ years of hands-on experience building production AI/ML systems and leading technical teams
• Expert-level Python programming skills with deep, proven experience in LangGraph, LangChain, and multi-agent orchestration patterns at scale
• Advanced prompt engineering expertise with large language models (Anthropic Claude, OpenAI GPT, Google Gemini), including systematic evaluation and optimisation of complex prompt chains
• Strong hands-on experience with RAG architectures, vector databases, and context-grounding techniques such as Model Context Protocol (MCP)
• Demonstrated ability to mentor engineers, establish technical standards, and translate architectural vision into production-grade, shippable AI services with a strong builder mentality

nice to have:

• Experience working in regulated environments, with familiarity with frameworks such as EU AI Act, DORA, or NIS2
• Practical knowledge of Kubernetes and GCP infrastructure within a CI/CD context
• German language skills