AI Engineer: Production Agent Infrastructure

Dex; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Dex, a partner to leading financial institutions, is hiring for an AI infra role focused on production agent reliability. You will own the evals, feedback loops, prompt engineering, and human-in-the-loop logic for high-stakes agent actions, while working across the full tech stack including Node and TypeScript.

You should bring production experience with agentic/LLM infrastructure and a pragmatic ML foundation, thriving in a fast-paced startup environment where data strategy evolves rapidly.

Qualifications

• Production experience building agentic or LLM infrastructure (evals, feedback loops, prompt engineering, fallbacks).
• Pragmatic ML foundation across supervised and self-supervised methods.
• Product-minded and full-stack; comfortable contributing to a Node/TypeScript stack.
• Strong system design skills; adaptable in a fast-paced assessment environment.

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

Human-in-the-loop

Node

TypeScript

ML foundations

Startup dynamics

Tools

Node.js

TypeScript

Job description

Dex, a partner to leading financial institutions, is hiring for an AI infra role focused on production agent reliability. You will own the evals, feedback loops, prompt engineering, and human-in-the-loop logic for high-stakes agent actions, while working across the full tech stack including Node and TypeScript.

You should bring production experience with agentic/LLM infrastructure and a pragmatic ML foundation, thriving in a fast-paced startup environment where data strategy evolves rapidly.