MLOps Engineer – Portfolio Optimisation and Customer Analytics Platform (Banking

This is a remote position. We are looking for an MLOps Engineer to support an enterprise analytics and optimisation platform within an international banking environment. The platform underpins pricing, capital allocation, and customer lifetime value decisions across multiple markets and product lines.It operates at scale with regular model retraining cycles and governed analytics processes. Analytical outputs feed both traditional reporting layers and LangChain and LangGraph based GenAI workflows that generate automated insights and scenario analysis. This role focuses on operationalising analytical models and ensuring stable, repeatable production workflows. Responsibilities Design and operate training and deployment pipelines for analytical and optimisation models Automate model retraining, validation, and promotion processes Ensure reproducibility and consistency across development, testing, and production environments Support scalable analytical workloads across cloud platforms Enable structured exposure of model outputs to LangChain and LangGraph workflows Monitor performance, stability, and reliability of ML pipelines Collaborate closely with data scientists and analytics teams to streamline experimentation to production Requirements Strong experience in MLOps or ML platform engineering Solid Python skills for automation and tooling Hands on experience with Docker and Kubernetes Practical experience with MLflow or similar model lifecycle management tools Experience with