Senior AI Engineer — Multi-Agent Systems & AI Platform

Senior AI Engineer – Agentic AI Systems & 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