Artificial Intelligence Architect

Role & responsibilities

• Design agentic AI architectures using multi-agent orchestration patterns (planner-executor, supervisor-worker, tool-using agents) • Define reference architectures for enterprise agent platforms integrating LLMs with systems of record (core banking, CRM, risk, payments). • Design audit-ready agent interactions, tool usage logs, and decision provenance. • Select and standardize frameworks (e.g., LangGraph, Google ADK, MCP, A2A patterns). • Hands-on expertise with agentic frameworks(orchestrators). • Experience with LLMs, prompt engineering, tool/function calling, memory management. • API-first integration, event-driven architectures, and data pipelines. • Exposure to AI quality metrics: task success rate, containment, FCR. • Experience on Google Cloud Platform (preferred)or equivalent hyperscaler. • Familiarity with secure cloud patterns, IAM, VPC design, and data protection. • Knowledge of MLOps / AgentOps, CI/CD, and observability. • Strong understanding of regulated financial services environments. • Proven experience implementing AI risk controls, model governance, and auditability. • Ensure alignment with FCA, PRA, data privacy, model risk management, and LBG internal policies. • Knowledge of banking processes: retail banking, lending, payments, compliance