DevOps Engineer Sanctions Tech Innovation
Role details
Job location
Tech stack
Job description
- Salary: Gross monthly salary between EUR 4,931 and EUR 7,043 (scale 09) for a 36-hour work week.
- Extras: a thirteenth month, 8% holiday allowance, and a 10% Employee Benefit Budget.
- Development budget: EUR 1,400 development budget per year for your growth and development.
- Hybrid working: a balance between home and office work (possible for most roles).
- Pension: decide for yourself the amount of your personal contribution.
Or view all our benefits.
Build and deploy production-ready data solutions supporting sanctions controls across the bank, improving detection quality and reducing false alerts with scalable AI-driven technology.
You & your role
Design, build and deploy production-grade data and AI solutions as a DevOps Engineer. You ensure secure, compliant and future-proof implementations across the full data lifecycle. You work closely with data scientists and engineers to translate ideas into production-ready solutions, from ingestion to deployment.
Examples from practice:
- Improving automated closure of false Level 1 detection alerts by optimising text-based detection logic.
- Supporting alert investigators with AI-generated insights for complex Level 2 detection alerts.
- Contributing to new monitoring models detecting sanction evasion through transaction behaviour., * Ensure stable and scalable deployment pipelines by building and maintaining CI/CD processes and validating integration across multiple data platforms.
- Drive collaboration with data scientists and stakeholders to translate analytical models into robust, compliant production environments.
- Improve data quality, performance and architecture by identifying issues and implementing structural enhancements.
You work on engineering and platform components that enable AI-driven sanctions solutions to move safely into production while ensuring scalability, compliance and reliability across systems.
Requirements
- HBO/WO work and thinking level with 5+ years DevOps or Data Engineering experience.
- 5+ years experience deploying models in regulated environments using Azure and CI/CD pipelines.
- Strong programming experience in Python and PySpark and workflow tools such as Airflow or MLflow.
- Proactive mindset.
- Strong sense of ownership.
- Collaborative skills.