AI Manager – Enterprise Applications (all genders) (m/w/d)

Roland Berger is one of the world's leading strategy consultancies with a wide-ranging service portfolio for all relevant industries and business functions. We cherish different perspectives and approaches and count on the diversity and authenticity of our employees. Driven by our values of entrepreneurship, excellence, and empathy, we at Roland Berger are convinced that business and society need a new sustainable paradigm that takes the entire value cycle into account. Our cross-competence teams work with our clients to successfully address the challenges of our time, today and tomorrow, across all industries and business functions. If you like to take the initiative and make a difference as part of a team, Roland Berger is the right place for you.

We are looking for an experienced AI Manager (all genders) to shape and run our enterprise AI orchestration platform within the Central IT Enterprise Applications team. This is an internal leadership role - not client-facing.

You will manage the end-to-end lifecycle of AI solutions - from use case intake and design to deployment, monitoring, and continuous improvement. You will ensure AI capabilities are securely and scalably integrated into our business applications while delivering tangible business value and meeting governance, security, and quality standards.

You will work at the intersection of business, data/AI, and infrastructure, acting as a key partner and technical leader for stakeholders across the organization.

Your key responsibilities are:

• Own the AI platform - take end-to-end ownership of Roland Berger's AI ecosystem, including the AI orchestration layer, AI agent frameworks, LLM integrations, and model routing infrastructure; shape the platform roadmap, own the platform budget, and drive build-vs-buy decisions in alignment with IT leadership

• Lead projects & products - manage end-to-end delivery of AI initiatives, balancing scope, timeline, and quality across cross-functional teams

• Manage vendors - primary contact for AI and cloud vendors; negotiate contracts, SLAs, and budgets; monitor performance and delivery

• Drive change management - lead adoption initiatives, manage stakeholder expectations, and embed AI capabilities sustainably across the organization

• Lead governance & compliance - establish responsible AI frameworks covering agent behavior, model lifecycle, data protection, and access control; ensure regulatory compliance with EU AI Act, GDPR, etc.

• Provide technical oversight - define architecture standards for AI orchestration and agent design; review solution proposals (no hands-on development)