Within the CTO division at Deutsche Börse Group, we operate and evolve the group-wide IT infrastructure — spanning networks, data centres, cloud environments, Group Data & Advanced Analytics, and Enterprise Architecture. As a technically focused AI Product Owner, you will serve as the critical bridge between product strategy and engineering execution for Agent Chain and Agent Hub, our event-driven, multi-agent orchestration platforms powering AI-assisted software development across 1,400+ developers and 25,000+ repositories. This role sits at the heart of our broader Group strategy and directly shapes how AI-driven software delivery operates at scale in a regulated financial market infrastructure.
Your responsibilities:- Own and continuously refine the sprint-level product backlog for Agent Chain and Agent Hub, decomposing strategic epics into technically detailed user stories, tasks, and Gherkin acceptance criteria that are immediately actionable by AI/ML and backend engineering squads.
- Collaborate directly with Senior AI Engineers and Senior Backend Developers to evaluate the technical feasibility of new agent capabilities, multi-agent orchestration patterns (LangGraph, agentic RAG, MCP integration), and backend services — including identity management, API design, and microservice decomposition.
- Define and validate quality gates for prompt chains, agent confidence thresholds, and output fidelity benchmarks; coordinate with DevSecOps and platform teams to ensure backend services, identity flows (OAuth 2.0/OIDC), Kubernetes deployments on GCP, and CI/CD pipelines meet enterprise-grade reliability and security standards.
- Translate EU AI Act, DORA, and NIS2 regulatory requirements into concrete technical acceptance criteria, ensuring every agent action is versioned, logged, auditable, and compliant prior to production release.
- Drive sprint planning, daily stand-ups, backlog refinement, and retrospectives with a technically informed perspective; remove impediments, clarify ambiguities in real time, and synchronise technical dependencies across Agent Chain and Agent Hub.
- Define, instrument, and monitor key technical product metrics — including agent accuracy, latency, API throughput, error rates, automation yield, and deployment frequency — to inform sprint-level prioritisation and continuous improvement.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related technical discipline, combined with 5+ years of experience in a technically oriented Product Owner, Technical Product Manager, or Engineering Lead role for AI/ML or platform products.
- Strong hands-on background in AI/ML systems, including practical experience with or deep understanding of LLM-based architectures, multi-agent orchestration frameworks (LangGraph, LangChain), prompt engineering, and Retrieval-Augmented Generation (RAG) patterns.
- Solid understanding of enterprise backend engineering, encompassing microservice architecture, RESTful and event-driven API design, OAuth 2.0/OIDC identity flows, and distributed systems patterns.
- Proficiency in reading, reviewing, and reasoning about Python and/or Java codebases, with the ability to participate credibly in architecture discussions and technical design reviews.
- Strong agile backlog management skills with proven experience working with Kubernetes, GCP, and CI/CD pipelines (GitHub Actions, Terraform), and a proven ability to decompose complex technical initiatives into well-defined, estimable, and testable increments.
- Experience in regulated industries, including familiarity with EU AI Act, DORA, and NIS2 compliance requirements.
- Hands-on experience with vector databases and context-grounding techniques (e.g. MCP).
- Certified CSPO or SAFe POPM certification.
- German language skills.