About the job

• ResponsibilitiesDesign end-to-end AI and data solutions: from data ingestion and modelling to deployment and integration into core business processes.
• Engage directly with customers and business stakeholders: understand strategic goals, translate them into AI use cases, and facilitate workshops that bridge data/AI capabilities and measurable business value.
• Define concepts for business challenges and decompose them into technically solvable components with clear scope, interfaces, and priorities.
• Shape target solution and business architectures (capability maps, process flows, value streams) and define reference architectures, patterns, and guardrails for AI solutions in cloud and hybrid environments.
• Lead solution design and give technical direction to development teams (data engineers, data scientists, software engineers), ensuring scalability, security, performance, and maintainability.
• Own the full solution lifecycle: from requirements and proof-of-concept to industrialisation, MLOps, monitoring, and continuous improvement.
• Create architecture artefacts (solution blueprints, context, sequence, and data-flow diagrams) documenting how AI solutions deliver business outcomes.
• Evaluate and select AI platforms, tools, and components, aligned with the existing IT and enterprise architecture.
• Decompose complex business challenges into technically solvable modules: define clear scopes, interfaces, dependencies, and priorities, and communicate the resulting solution approach convincingly back to the business and the customer.

• RequirementsDegree in (business) informatics, computer science, mathematics, engineering, natural sciences, or a comparable field.
• 3–5 years in data & AI projects across the full lifecycle, from requirements engineering to operationalisation.
• Proven experience designing data/AI architectures on a major cloud platform (Azure, AWS, or GCP), including data platforms, pipelines, and APIs (event-driven architectures, microservices).
• Working knowledge of MLOps concepts (CI/CD for models, versioning, monitoring, retraining).
• Strong skills in statistics, machine learning, and advanced analytics, with a solid grounding in data modelling, data management, and governance.
• Ability to translate business requirements into technical solutions and clear architecture artefacts.
• Experience directing development teams in customer projects.
• Confident customer-facing communicator, able to explain complex technical concepts to business and technical audiences up to C-level, in fluent English and German at B2 level or above is a strong advantage.
• Independent, solution-oriented working style with strong team spirit.