Senior AI Engineer - Agentic AI Systems and Platform Our client is building the AI operating layer for wealth management, enabling financial institutions to deliver more personalised advice, streamline operations, and scale expertise through intelligent AI systems. As a Senior AI Engineer, you will play a key role in designing, building, and deploying next-generation AI products powered by large language models, agentic workflows, advanced retrieval systems, and enterprise-grade AI infrastructure. This is a hands-on engineering position for someone who enjoys solving complex problems at the intersection of AI research and software engineering. You'll help transform cutting-edge AI capabilities into production-ready solutions that can be trusted within highly regulated environments. What You'll Be Doing Agentic AI & Workflow Orchestration Build and deploy advanced AI agent workflows using LangGraph and modern orchestration frameworks Design systems capable of planning, reasoning, tool usage, and autonomous task execution Develop scalable agent architectures for complex business processes and AI-driven automation Retrieval, Memory & Knowledge Systems Design and optimise enterprise-grade RAG solutions Build AI memory frameworks that enable context persistence and long-running workflows Develop knowledge graph solutions and leverage graph databases to enhance retrieval and reasoning AI Research & Emerging Capabilities Develop AI-powered research agents and web intelligence tooling Evaluate and implement emerging AI techniques, models, and frameworks Contribute to voice-to-voice and multimodal AI experiences AI Governance, Evaluation & Reliability Build evaluation and benchmarking frameworks to measure AI system performance Implement LLM-as-a-Judge methodologies and automated testing pipelines Establish governance, observability, monitoring, and reliability standards for production AI systems What We're Looking For Essential Skills & Experience 6+ years of experience building and deploying AI, machine learning, or data-driven software systems Strong Python engineering experience with a proven track record of delivering production applications Hands-on experience developing LLM-powered applications and agentic workflows Experience with LangGraph, LangChain, AutoGen, CrewAI, or similar agent frameworks Strong understanding of RAG architectures, vector databases, and retrieval systems Experience designing scalable AI workflows and multi-step reasoning systems Familiarity with AWS, Azure, or GCP cloud environments Excellent problem-solving skills and a systems-thinking approach Desirable Experience Model fine-tuning and foundation model optimisation AI memory architectures and persistent agent state management Knowledge graphs and graph databases such as Neo4j or Amazon Neptune Evaluation frameworks, benchmarking, and LLM-as-a-Judge methodologies Web research agents and autonomous information-gathering systems Voice AI, speech-to-speech, or multimodal applications AI governance, compliance, and risk management frameworks Experience within financial services, wealth management, or other regulated industries