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You are shaping AI technology across Eventim — defining the direction, standards, and architectural foundations that make AI a scalable and trusted part of our products and platforms. You think in systems and roadmaps, but you also understand what it takes to turn ideas into working solutions.
You have probably started your career as a coder and still bring a hands-on mindset to your work. You are comfortable diving into technical details, reviewing designs, and challenging assumptions, while also stepping back to make long-term technology decisions. Operating at the intersection of strategy and execution, you translate business ambition into clear AI technology choices and architectures that teams can confidently build on.
You work closely with engineers, architects, product leaders, and executives to ensure AI adoption is purposeful, integrated, and delivers real value — today and in the future.
What to expect
- Define and evolve Eventim’s AI technology strategy and roadmap, aligned with business goals and the broader enterprise architecture.
- Establish AI architecture principles, reference architectures, and standards to enable responsible, secure, and scalable AI adoption.
- Provide architectural and technical leadership for AI/ML solutions, including model lifecycles, data flows, deployment patterns, and system integration.
- Evaluate and guide the selection of AI technologies and platforms, such as LLM frameworks, vector databases, MLOps tooling, and cloud-native AI services.
- Collaborate closely with data, cloud, platform, and application teams to embed AI capabilities into Eventim’s products and technology landscape.
- Identify opportunities for reuse and standardization, building shared AI services, accelerators, and patterns that enable teams to move faster.
- Partner with business and product stakeholders to assess AI opportunities, shape use cases, and translate them into sustainable technical solutions.
- Act as an advisor and enabler across the organization, promoting AI best practices, architectural guidance, and a common understanding of AI capabilities.
What you’ll need
- A strong technical foundation, likely starting your career as a software engineer or hands-on technologist, with the ability to still engage deeply in technical discussions and design decisions.
- Extensive experience in technology or solution architecture roles, with several years focused on AI/ML systems in production environments.
- Proven ability to shape AI technology direction and architecture, not just design individual solutions — including setting principles, standards, and long-term roadmaps.
- Hands-on experience with modern AI/ML technologies, such as LLM platforms, embeddings, vector databases, and MLOps practices, with a pragmatic understanding of their trade-offs.
- Solid knowledge of at least one major cloud platform (AWS, Azure, or GCP), including AI services, security concepts, and operational considerations.
- Strong understanding of data architectures, APIs, integration patterns, and distributed systems, enabling AI solutions to integrate cleanly into complex enterprise landscapes.
- Experience working within enterprise architecture contexts, including use of architecture tooling (e.g. LeanIX, Ardoq), without losing delivery focus.
- Ability to bridge strategy and execution — comfortable discussing vision and roadmaps with leadership while earning trust through technical depth.
- Clear and confident communication skills, with the ability to influence cross-functional teams and explain complex topics to both technical and non-technical audiences.
- A curious, pragmatic, and delivery-oriented mindset, with a strong sense of ownership; fluent English required, German is a plus.
