Technical AI Business Analyst

Role: Technical AI Business Analyst – GenAI / Agentic Systems

Location: London Hybrid (1-3 days onsite)

Rate – £250 – £600 Per Day inside IR35

Overview

We’re looking for a highly capable Technical AI Business Analyst with hands-on experience delivering production-grade GenAI solutions, particularly those leveraging multi-agent architectures using frameworks like LangChain, LangGraph, and OpenAI’s Agent Framework.

You will join a forward-thinking team within a major financial institution\’s Treasury and Liquidity function, helping to shape and deliver AI-powered systems that streamline document handling, decision workflows, and internal knowledge processes.

What You’ll Do

• Work closely with AI engineers and Treasury SMEs to define end-to-end use cases involving multi-agent AI systems.
• Translate business needs into detailed technical workflows using LangGraph, ensuring agents interact via clear logic and shared state.
• Shape document-based GenAI solutions, including RAG pipelines, prompt engineering, and integration with internal APIs.
• Help orchestrate tools using OpenAI function calling, vector databases (e.g. Pinecone, Weaviate), and knowledge graphs.
• Collaborate on the deployment of AI agents as secure microservices using Azure Kubernetes Services (AKS) and monitor system performance.
• Draft structured documentation, user manuals, and internal process maps for end users and engineering handover.

Must-Have Skills

• Strong experience with LangChain, LangGraph, or equivalent multi-agent orchestration frameworks.
• Solid understanding of RAG (Retrieval-Augmented Generation) architecture, including chunking strategies, embeddings, and prompt design.
• Proven ability to define and coordinate agent interaction protocols, fallback logic, and tool use within LLM systems.
• Experience integrating OpenAI (or Anthropic) models with enterprise data via APIs and tools.
• Comfortable deploying systems in Azure (AKS, App Services, ML Endpoints) with CI/CD awareness.
• Ability to work with AI engineers and business stakeholders to bridge the gap between conceptual use cases and deployed AI solutions.
• Background in Treasury, Liquidity, or financial services is ideal but not essential if candidate has strong document-based AI solutioning experience.