ai engineer in banking

The company builds and licenses AI agents that automate critical customer lifecycle workflows for major financial institutions. Its production agentic systems handle complex, high-stakes banking processes.

• Design and implement agent reliability infrastructure, including evals, feedback loops, prompt engineering, and fallbacks;
• Build and maintain human-in-the-loop decision logic for high-stakes agent actions;
• Take ownership of proprietary supervised and self-supervised ML models, applying recent academic work pragmatically;
• Contribute across the full agentic and software stack, including Node and TypeScript;
• Shape the evolving data strategy for production AI agents in a rapidly growing environment.

• Production experience building and maintaining agentic or LLM infrastructure, including evals, feedback loops, prompt engineering, fallbacks, and human-in-the-loop decision logic;
• A pragmatic ML foundation across supervised and self-supervised methods;
• A product-leaning and full-stack mindset, with comfort contributing to a Node and TypeScript software stack;
• Strong system design capabilities;
• Proven adaptability in a technical assessment, such as TypeScript;
• Ability to thrive in a fast-paced startup environment, execute at pace, and own an area while data strategy evolves.

• Salary up to £130k.