Vice President of AI Automation leading multidisciplinary AI teams at Synchrony. Focusing on building and maintaining a scalable AI automation platform and enhancing customer experiences through AI.
About the role
- AI Technology Strategy and Architecture Lead shaping AI technology strategy and architecture at Eventim. Collaborating with teams to ensure purposeful and integrated AI adoption.
Responsibilities
- 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.
Requirements
- Strong technical foundation, typically starting your career as a software engineer or hands-on technologist, with the ability to 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), while maintaining 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.
Benefits
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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