Financiële diensten
Senior DevOps/MLOps Engineer - end-to-end deployment, CI/CD, and observability for AI/LLM services
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Role context
In a large banking organization, the Senior Machine Learning Ops Engineer supports a data science squad in the Business Lending domain by helping deliver and operate AI services. The work is performed within a cross-functional environment that includes data scientists, architects, engineers, and a platform team, and it focuses on enabling dependable AI services in Production.
Responsibilities
This role owns the end-to-end deployment lifecycle for AI services, including CI/CD pipelines, containerized deployments, observability, and environment management across DEV/UAT/PROD. It functions as a technical bridge between data science and platform engineering to ensure that GenAI and agentic workloads run reliably in Production. The role also designs and maintains infrastructure components for LLM-based and agentic applications, including container orchestration and API serving layers, and supports cloud integration for AI capabilities. Proactive participation in team design sessions and improvements to platform and MLOps practices are expected.
Business value
The position contributes to data-driven decision support in Domestic Business Lending, including AI-supported retention strategy development, portfolio management decision support through simulation and forecasting, and acceptance strategy definition for new applications using AI-driven simulation approaches.
Eisen
- No ZZP allowed
- Language: English and Dutch mandatory
Wensen
- Working experience with data science teams
- Data engineering tooling, preferably on Azure Databricks
- Experience with setting up a "gold standard"/blueprint/way of working for ML models
- Experience with implementing feature stores
- Experience within the banking sector
- Knowledge of Kubernetes/Docker
- Experience with LangGraph / LangChain