AI Engineer (up to £130k)

Dex; Greater London; On-site; GBP 80,000 - 120,000; Full time

Job summary

Dex partners with a leading AI-enabled fintech supplier to deliver production-grade agentic systems for major financial institutions. The role focuses on ensuring reliability and scalability of production agents across evals, feedback loops, prompt engineering, and fallbacks.

You will design human-in-the-loop logic and own the integration across the full agentic and software stack, blending AI engineering with pragmatic ML using Node.js and TypeScript.

Qualifications

• Experience with agentic/LLM infrastructure including evals, feedback loops, prompts.
• Strong ML background in supervised and self-supervised methods.
• Hands-on with Node.js and TypeScript; full-stack mindset.
• Excellent system design skills and ability to work in fast-paced environments.
• Comfort adapting as data strategy evolves in a startup context.

Responsibilities

• 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.

Skills

Agent infra

LLM infra

Prompt engineering

Feedback loops

Human-in-the-loop

ML foundations

System design

Startup mindset

Tools

Node.js

TypeScript

Job description

This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

The role

This company builds and licenses AI agents that automate critical customer lifecycle workflows for major financial institutions. They run real agentic systems in production, tackling long, high-stakes banking processes. Backed by leading VCs, they're scaling rapidly with significant traction.

It is not a siloed research role. You will own the infrastructure that keeps these production agents reliable: the evals, feedback loops, prompt engineering, and fallbacks. You'll also design the human-in-the-loop logic, deciding when an agent acts and when a person steps in. It's a product-leaning seat, blending AI engineering with pragmatic ML, building across the full agentic and software stack.

The work

• 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.

What You Bring

• Production experience building and maintaining agentic or LLM infrastructure: evals, feedback loops, prompt engineering, fallbacks, and human-in-the-loop decision logic.
• A pragmatic ML foundation across supervised and self-supervised methods.
• Product-leaning and full-stack in mindset; comfortable contributing to a Node and TypeScript software stack.
• Strong system design capabilities, with proven adaptability in a technical assessment (e.g., TypeScript).
• Thrives in a fast-paced startup environment, executing at pace and owning your lane while data strategy evolves.