Data & AI Expert Consultant

Imagine this: A MedTech customer has a great AI idea.

Everyone is excited. No one is ready.

A MONDAY, SOMEWHERE IN A CONFERENCE ROOM

The business sees enormous potential. IT is asking about integration, security and operations. Quality wants traceability and governance. Management expects a roadmap. Somewhere between excitement, uncertainty and time pressure lies a critical architecture decision – without anyone to make it properly.

That’s where we need you. Someone who combines technical depth, consulting experience and the ability to make decisions. Someone who knows when a use case has real potential – and when the data and process foundations need to be in place before anyone starts talking about LLMs.

Your Responsibilities

You don’t build AI showcases.

You build solutions that run in production.

• Bring structure to complex AI initiatives
• Design target architectures for Data/AI platforms on Azure, Databricks, Snowflake or AWS – including security, governance and scalability
• Design LLM and RAG architectures for real-world operations
• Azure OpenAI, vector databases, LangChain, LangGraph. The key question isn’t whether the prototype is impressive – it’s whether the solution can be operated reliably in production
• Bridge the gap between C-level and engineering
• Explain roadmaps to executives. Then discuss data flows, model deployment, monitoring and CI/CD with engineering teams
• Lead through expertise, not hierarchy
• Coach consultants and engineers, connect colleagues across locations and establish best practices. You lead through clarity, not titles
• Strengthen our Data & AI portfolio
• Evaluate technologies, develop reference architectures, and build reusable templates and standards for customer projects

What You Bring

• Several years of experience in Data, Cloud, Software or AI architecture, with a strong understanding of modern platform architectures around Azure Data Services, AWS, Databricks and Snowflake
• The ability to identify patterns in complex customer requirements, consciously weigh trade-offs and make architectural decisions that work in real-world operations – not just in a PoC
• Generative AI is no longer an experimental playground for you, but a productive toolbox: you have already implemented LLM-based systems (e.g. with Azure OpenAI) and have hands-on experience with RAG architectures and vector databases
• Experience with MLOps and deployment patterns, including model serving, monitoring and CI/CD for AI workloads using tools such as MLflow, Azure ML, LangChain or LangGraph
• You feel at home in a consulting environment: pre-sales, discovery, solution design, effort estimation and technical presentations are part of your everyday work. You can bridge the gap between architecture, business and engineering
• You understand that good architecture also means leadership and have experience making technical decisions visible, providing direction to teams and embedding best practices into projects
• Very good German skills (C1) and good English skills (B2)
• Willingness to travel frequently in Germany, or to relocate to Germany