AI Data Engineer (m/f/d)

The Woodmark Group is a leading consulting organization specializing in AI, data, and analytics. We inspire people through our passion for data and innovation while supporting organizations on their digital transformation journey. Living our values of respect, openness, trust, and care fosters an excellent corporate culture and forms the foundation of our success.

As part of a team, you’ll develop AI and ML models and the corresponding data pipelines. In doing so, you’ll think not only in terms of models, but also in terms of scalable systems. You’ll design robust, production-ready AI architectures and ensure their sustainable integration into existing cloud and data environments.

Translating and Implementing Requirements: Based on business requirements, you’ll design scalable AI and data architectures. You’ll use ML inference techniques, perform fine-tuning, and develop effective prompt engineering strategies. Drawing on your experience with AWS or Azure cloud environments, you’ll design viable target architectures for AI use cases (e.g., RAG architectures, vector databases, agent-based systems) and seamlessly integrate them into existing enterprise architectures. You’ll use Infrastructure-as-Code (e.g., Terraform, CloudFormation, Bicep) to build reproducible, scalable, and secure environments. You’ll leverage your knowledge of MLOps, DevOps, and platform architectures to make AI solutions production-ready.

Taking on Responsibility: You’ll assume technical responsibility for smaller projects or subprojects, particularly for architectural design and technical implementation. You’ll evaluate technology decisions in terms of scalability, security, governance, and costs.
With your understanding of architecture, you’ll support less experienced team members as a technical sounding board.

Communication is key: You’ll be in constant, close communication with

• the business units and architects to coordinate project-related matters
• your clients to ensure transparency in architectural decisions and manage expectations
• your project team to ensure technical excellence and project success
• the Woodmark team to share knowledge about AI architectures, cloud patterns, and best practices.

Project Experience: You have at least 2 years of project experience in the data or cloud engineering field and a solid understanding of modern data and AI architectures. You’re not only familiar with services but also understand how they interact within scalable system landscapes.

Expertise is a given: You have

• At least 3 years of experience in data engineering or cloud engineering
• At least 2 years of experience in machine learning or AI
• Very strong knowledge of Python (Java or Scala optional)
• Solid experience with AWS or Azure, as well as AI cloud services such as Bedrock or Azure OpenAI
• Experience with Infrastructure as Code (e.g., Terraform, CloudFormation, Bicep)
• Knowledge of container and orchestration technologies (Docker, Kubernetes, EKS, AKS)
• Experience with workflow management systems such as Airflow, AWS Step Functions, or comparable services
• Ideally, experience with vector databases, RAG architectures, or agent-based AI systems
• A strong understanding of non-functional requirements such as performance, security, compliance, and cost optimization

Intrinsic interest in AI innovations: You actively follow technological developments in the AI market and critically evaluate new services and architectural approaches in terms of their practical benefits.

Stakeholder-oriented thinking helps us move forward: You have experience collaborating with stakeholders at various levels from business units to IT architecture and can communicate complex technical issues in a structured manner.

Support the “Making of a Star”: You actively support other Woodmarkers in building AI and architecture expertise and proactively contribute your knowledge to the team.

Fluency in German and English: You are comfortable working on German-language projects and can clearly present technical documentation and architectural concepts in English as well.