Role: ML & AI Engineer Location: London,UK Job type : Contract Mode of work : Hybrid -2 days onsite in a week JD: Key responsibilities \* Developing and provisioning of infrastructure that support agentic workflows across both Azure and GCP \* Data science expertise to help shape the agentic solution design of Coach AI as well as target state AI Assistant \* Creation of agent integration patterns to fulfil and action on behalf of customers by leveraging Bank systems \* Development of new AI products for the Conversational Banking Lab, including but not limited to: \* Agent summarisation - bespoke features to summarise nuanced conversations \* App search evolution - transforming the existing vector search functionality into a fully generative experience and transition to single experience point \* Evaluation methods - continued automation of both deterministic and generative conversations in a scaled and simulated way Key Skills/Knowledge: Must haves \* Python literacy - min 2years+ working on production grade LLM based applications \* Software Engineering - strong understanding of microservices architecture, CI/CD pipelines, event driven architecture \* AI Engineering - RAG pipelines, prompt engineering, VertexAI experience, LLMOps and runtime evaluation/monitoring \* Data engineering - scaled data pipelines using python/spark. GCP native services: BQ, Spanner, Dataflow, Firestore Nice to haves \* AgenticAI - Langgraph, ADK, CrewAI, multi-agent architectures - experience in building deployable solutions, not jupyter notebooks \* Data ontologies - graphical approaches to data storage + retrieval • Exposure to Agile/Scrum methodologies