AI Engineer (up to £130k)

Dex; Greater London; Presencial; GBP 90.000 - 120.000; Jornada completa

Descripción de la vacante

Dex 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. Dex is backed by leading VCs and scaling rapidly with significant traction.

This is not a siloed research role. You will own the infrastructure that keeps production agents reliable: evals, feedback loops, prompt engineering, and fallbacks.

Formación

• Experience building and maintaining agent or LLM infrastructure (evals, feedback loops, fallbacks).
• Pragmatic ML foundation across supervised and self-supervised approaches.
• Product-focused, full-stack mindset with Node/TypeScript contribution.
• Strong system design and ability to work in a fast-paced startup.
• Ability to own data strategy for production AI agents.

Responsabilidades

• 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.
• Own 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.

Conocimientos

LLM infrastructure

Evals

Feedback loops

Prompt engineering

Human-in-the-loop

Node.js

TypeScript

System design

Startup pace

Herramientas

Node.js

TypeScript

Descripción del empleo

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.

This 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.

Why this role

This is a rare, high-impact AI engineering role at a company running real agentic systems in production.