Job Description

At Eventim, we’re transforming how technology shapes live experiences — building the world’s leading event-tech and ticketing platform through excellence, innovation, and ownership. As part of this journey, we’re bringing AI into every product — helping fans, artists, and promoters connect in smarter, more seamless, and unforgettable ways.



We are seeking a skilled

Enterprise AI Architect

(m/f/d) to shape Eventim’s AI architecture and accelerate AI adoption across the organization. In this role, you’ll define our AI vision, design scalable and secure architectures, and guide teams in building and integrating AI solutions. You’ll combine strategic thinking with hands-on technical leadership to ensure AI becomes a reliable and impactful part of our enterprise ecosystem.

What to expect

Develop Eventim’s enterprise-wide AI architecture, reference designs, and standards for responsible and scalable AI adoption. Provide architectural leadership for AI/ML solutions, including model design, data flows, deployment patterns, and platform integration. Evaluate and select AI technologies such as LLM frameworks, vector databases, MLOps platforms, and cloud-native AI services. Collaborate with data, cloud, and application teams to integrate AI capabilities into Eventim’s products and systems. Identify reusable components and build shared AI services, accelerators, and patterns that streamline AI development across teams. Work with business stakeholders to assess AI opportunities, shape use cases, and translate them into robust technical architectures. Promote awareness of AI capabilities, standards, and best practices across the organization.

What you’ll need

8+ years in architecture roles, including 3–5 years focused on AI/ML architecture. Proven experience designing, deploying, and scaling AI/ML solutions in enterprise environments. Strong understanding of enterprise architecture frameworks and tooling (e.g., LeanIX, Ardoq). Hands-on expertise with AI/ML frameworks, LLM platforms, embeddings, vector databases, and MLOps practices. Solid knowledge of AWS, Azure, or GCP, including relevant AI services and security standards. Deep understanding of data architecture, APIs, integration patterns, and microservices. Ability to clearly communicate complex concepts and influence cross-functional teams. * A strategic, curious, and delivery-focused mindset; English required, German a plus.