Responsibilities Design, build and validate agentic AI workflows, including multi‑step reasoning and tool‑use orchestration. Analyse agent and model behaviour to assess robustness, safety, error propagation and end‑to‑end decision quality. Integrate APIs, external tools, plugins and system connectors required for agent operations. Develop and execute evaluation approaches for LLMs and agentic systems, including scenario tests, benchmarks and automated pipelines. Assess retrieval components, vector databases, memory systems and workflow reliability. Apply Responsible AI principles and regulatory expectations to model behaviour, documentation and control standards. Partner with data science, engineering, architecture and risk teams to ensure safe and compliant AI deployment. Collaborate with other departments' data scientists to understand modelling intent, technical assumptions and workflow logic. Contribute to AI/ML proof‑of‑concept (POC) initiatives to strengthen evaluation practices ...