Production AI Agent Engineer (LLM Infra)

Dex; Greater London; On-site; GBP 110,000 - 180,000; Full time

Job summary

Dex’s partner company is engineering AI agents that automate critical customer lifecycle workflows for major financial institutions, operating production-grade agentic systems. You will own the infrastructure ensuring production agents remain reliable, including evals, feedback loops, prompt engineering, and fallbacks, while shaping human-in-the-loop logic for high-stakes actions.

The role blends AI engineering with pragmatic ML across the full stack, contributing to the data strategy and

Qualifications

• 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.

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

Agentic infrastructure

LLM infrastructure

Node.js

TypeScript

System design

Tools

Node.js

TypeScript

Job description

Dex’s partner company is engineering AI agents that automate critical customer lifecycle workflows for major financial institutions, operating production-grade agentic systems. You will own the infrastructure ensuring production agents remain reliable, including evals, feedback loops, prompt engineering, and fallbacks, while shaping human-in-the-loop logic for high-stakes actions.

The role blends AI engineering with pragmatic ML across the full stack, contributing to the data strategy and