Technical Product Owner – AI Agent

For over 50 years, SimCorp has worked closely with investment and asset managers to become the world’s leading provider of integrated investment management solutions. It is an independent subsidiary of the Deutsche Börse Group, leveraging combined strengths following a recent merger to offer a full suite of front-to-back investment management solutions. SimCorp employs over 3,000 professionals from diverse backgrounds across more than 20 international offices.

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field.
• Over 8 years in software product development with hands-on software engineering experience.
• Several years as a (Technical) Product Owner, Product Manager, or Tech Lead.
• Strong engineering background to discuss architecture, APIs, integrations, and non-functional requirements with peers.
• Solid understanding of software development lifecycle and engineering tooling: source control, CI/CD, work-item tracking, code review, testing, release management.
• Working knowledge of AI/LLM products including agent capabilities, tool calling, prompt behavior, and model limitations.
• At least 1 year of hands-on experience using AI coding agents such as Claude Code or Codex.
• Familiarity with open-source agents (e.g., OpenCode, Hermes, OpenClaw) and fast-moving agent ecosystem.
• Passion for AI space and ability to stay current with market trends and best practices.
• Proven ability to write crisp user stories and acceptance criteria for complex technical features.
• Data-driven prioritization skills using adoption metrics, user feedback, and impact measurement.
• Experience with Agile development and distributed international teams.
• Excellent stakeholder management and communication skills to align engineering, architecture, and business perspectives.
• Excellent English communication skills, both written and spoken.

Business value:

• Translate user and stakeholder needs into clear, implementable features, user stories, and acceptance criteria.
• Own and prioritize the product backlog to maximize agent value across the software development lifecycle.
• Support the team during refinement, planning, implementation, and feature acceptance.
• Clarify requirements early and challenge assumptions to improve business and technical quality.
• Validate and test delivered stories and features against user needs and quality expectations.
• Measure adoption, usefulness, and impact of agent capabilities; adjust priorities based on data and feedback.

Technical quality:

• Work closely with architects and tech leads to ensure solutions align with the target architecture and long-term product vision.
• Make technical constraints, architectural decisions, and non-functional requirements visible in prioritization decisions.
• Evaluate technical implications, dependencies, risks, and implementation options for new capabilities and integrations.
• Balance feature delivery with maintainability, scalability, and technical debt reduction.

Capability development and teams' growth:

• Champion AI usage across engineering teams to accelerate delivery and improve efficiency.
• Accelerate onboarding and growth of team members through coaching and hands-on guidance.
• Promote knowledge and adoption of the agent's capabilities throughout the organization.

Management and stakeholder alignment:

• Partner with engineering and product management leadership on backlog, capacity, dependencies, quality signals, and delivery risks.
• Act as the bridge between product management, engineering, architecture, and business stakeholders.
• Mentor senior and lead engineers, QA engineers, and product owners; serve as subject-matter expert for agent capabilities and workflows.