Job Description

AI Engineer | Agentic AI, LangGraph, LLMs, Python, RAG, Multi-Agent Systems | Banking Technology | London / Hybrid | up to 125k Salary + Benefits

Build production-grade agentic AI systems that transform enterprise environments.

This is an opportunity to join a cutting-edge banking technology environment delivering next-generation AI applications powered by agentic systems, large language models, and advanced NLP. You’ll be working on real-world systems designed to improve decision-making, automate workflows, and enhance user experiences at scale.

As an AI Engineer, you’ll design and build multi-agent architectures, agent-to-agent communication frameworks, and LangGraph workflows, developing scalable, production-ready AI systems. This is not an experimental role—you’ll be delivering robust, enterprise-grade solutions that operate in live environments with high performance, reliability, and security requirements.

You’ll work across Python, asynchronous programming, OpenAI SDK, LangGraph, RAG pipelines, and distributed systems, building intelligent systems that combine LLMs with structured workflows. You’ll also design and implement retrieval-augmented generation pipelines, including document processing, embedding generation, and retrieval evaluation, alongside guardrails, observability, and fallback mechanisms to ensure safe and reliable AI performance.

The role involves building and deploying cloud-native AI systems across AWS, Azure, or GCP, using technologies such as Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code to deliver scalable and cost-efficient solutions. You’ll collaborate with cross-functional teams to integrate AI systems with APIs, backend services (Node.js, REST, GraphQL), and enterprise platforms, ensuring seamless system integration.

We’re looking for engineers with strong experience in Python and asynchronous programming, hands-on experience building agentic AI systems or working with frameworks such as LangGraph and OpenAI SDK, and a solid understanding of distributed systems and cloud architecture. Experience with LLMs, NLP pipelines, RAG systems, and multi-agent coordination is essential, along with the ability to build production-grade systems rather than prototypes.

Exposure to Node.js, API design, frontend integration, or financial services environments is beneficial but not essential.

This is a high-impact opportunity to work at the forefront of agentic AI and enterprise AI engineering, building systems that push the boundaries of what LLM-powered applications can achieve in real-world environments.

Apply now by sending your CV or reach out to Nathan Laidlaw from Transparent Tech for a confidential discussion.