As AI Technology Expert (m/f/d) you serve as the technical bridge between G+D Currency Technology and the G+D group’s central AI Hub. You ensure alignment on AI standards, evaluate technical feasibility, and support teams in implementing AI solutions efficiently and in line with central guidelines. In this role, you act as the first point of contact for technical AI questions, helping stakeholders understand data requirements, solution options, and integration pathways.You add value by providing deep technical expertise, assessing data pipelines and quality, and defining technical best practices to accelerate AI development and ensure consistency across the organization.You will report to the Currency Technology AI Lead, with close collaboration with the central AI Hub.

Your Responsibilities:

• Act as the technical interface between the division and the AI Hub, ensuring compliance with shared AI standards and architectures
• Evaluate the technical feasibility of AI use cases including data availability, data quality, and required pipelines
• Define, document, and promote technical best practices for AI development, deployment, and lifecycle management
• Support teams with technical guidance, prototypes, troubleshooting, and tool recommendations for AI use cases
• Assess integration needs and work closely with IT, and central platform teams
• Identify opportunities to reuse central models, components, and pipelines
• Provide technical input early in the use case lifecycle to support scoping and solution design
• Follow emerging AI technologies and share insights within the internal AI community

Your Qualifications:

• University degree in computer science, data science, engineering, mathematics, or similar
• Proven years of experience in AI engineering, ML engineering, or related technical roles
• Strong understanding of AI/ML concepts, model lifecycle, and MLOps principles
• Experience with modern data and AI platforms (e.g., Azure, MS Fabric, SAP data platforms, Databricks)
• Solid knowledge of data pipelines, ETL, and data quality assessment
• Proficiency with Python and common Data Science- and ML-frameworks (e.g. Pytorch, Tensorflow, Scikit-Learn…)
• Ability to switch quickly between diverse use cases and business domains
• Strong communication skills to support both technical and non‑technical stakeholders
• Highly flexibility in collaboration with teams in different time zones
• Business‑fluent in English; German is a plus