AI Engineer - FinTech - London
Role details
Job location
Tech stack
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.
Requirements
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.