Technical AI Product Owner - Agent Chain & Agent Hub (f/m/d)

Your career at Deutsche Börse Group 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.

Your profile

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.

Nice to have: 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. #J-18808-Ljbffr