• Connect the framework: Integrate a modular simulation optimisation framework with production AnyLogic models, databases, APIs, and plant-data environments. • Turn questions into use cases: Translate operational questions — scheduling, resource allocation, operating parameters, energy, logistics, throughput — into simulation and optimisation use cases. • Build in Java: Develop and maintain Java-based components that execute scenarios, marshal inputs, parse outputs, and enable reliable optimisation runs. • Make results credible: Define and validate simulation input/output data contracts and business KPIs, ensuring recommendations are reproducible and usable by operational stakeholders. • Optimise smartly: Apply the right optimisation approaches for real-valued, scheduling, selection, and multi-objective problems — and design efficient experiments for long-running simulations. • Prove the value: Validate recommendations against live models, quantify operational benefit, and support the transition from prototype to a repeatable operational process. • Operationalise it: Contribute to dashboards, recurring study scheduling, workflow integration, technical documentation, and knowledge transfer. • Collaborate closely: Work with client stakeholders and the wider delivery team to prioritise delivery, resolve issues, and maintain technical quality.