Job Title: AI & Data Engineer [Interim]
Location: (Hybrid) Rotterdam
Engagement: Full-time, 5 days a week
Contract duration: 3-6 months (possibe extension)
Start date: ASAP
Context
A large, international company in the engineering sector is scaling production-grade AI across the organization. The Data & AI Platform team is expanding delivery capacity and is looking for an interim Data & AI Engineer who can step in immediately, take ownership of AI use cases end-to-end, and accelerate adoption across business teams on an Azure + Databricks foundation.
This is a hands-on delivery role with high autonomy: you will build, ship, operate, and improve AI solutions in productionwhile introducing reusable components and pragmatic best practices that raise the bar across the platform.
What you'll do
- Deliver AI use cases end-to-end: from ingestion and feature engineering to model/agent development and production rollout.
- Design and operate Databricks lakehouse pipelines (batch and streaming) using Spark/SQL/Delta Lake, including monitoring and data quality controls.
- Build AI solutions on the platform, including:
- RAG patterns (retrieval, chunking, embeddings, evaluation)
- tool-using agents and orchestration approaches
- prompt strategies and testing/guardrails
- (where relevant) custom ML models and supporting pipelines
- Productionize and run what you build: reliability, observability, cost control, and operational hygiene.
- Enable other teams by creating reusable components, templates, and delivery standards.
- Work with governance and compliance: align with AI governance requirements and ensure solutions are secure and auditable.
- Collaborate with stakeholders across IT and the business to translate needs into working solutions and clear delivery increments.
What success looks like (first weeks)
- Rapidly understand the current Azure/Databricks landscape and delivery priorities.
- Pick up 12 active use cases and move them toward production-quality standards.
- Strengthen delivery patterns (templates, evaluation approach, monitoring, data quality checks).
- Create momentum with visible working increments and pragmatic documentation.
Required experience
- Proven experience as a Data Engineer / Data & AI Engineer delivering solutions into production environments.
- Strong hands-on Databricks expertise: Spark/SQL, Delta Lake, Jobs/Workflows, performance tuning.
- Strong Python + SQL for data engineering and AI/ML workflows.
- Experience building data pipelines with quality checks and operational monitoring.
- Practical experience with LLM-based solutions (RAG and/or agents), including prompt strategies and evaluation approaches.
- Comfortable working independently in an interim context: you can own delivery, communicate clearly, and unblock yourself.
Nice to have
- Azure services exposure (e.g., Azure ML, Azure OpenAI, Key Vault, Functions, ADF).
- LLM toolkits (LangChain, Semantic Kernel), prompt evaluation frameworks, early LLMOps patterns.
- CI/CD (GitHub Actions) and Infrastructure-as-Code (Terraform).
- ML frameworks (PyTorch, TensorFlow, scikit-learn) where needed.
Why this assignment
- Immediate impact: deliver AI use cases into production on a modern Azure Databricks platform.
- High ownership and autonomy: a true interim role where delivery outcomes matter.
- Real-world relevance: projects tied to large-scale operations in a complex, safety- and compliance-aware environment.
