Job description
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 production—while 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 1–2 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.
or
All done!
Your application has been successfully submitted!
