Example listing with a fictional company — for demonstration only, not a live vacancy.

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LLM Engineering

AI Application Engineer

Nimbus Systems

LondonRemoteMid-levelFull-time$120k–150k
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Example — Signed-In Preview

Your Match

This is what a signed-in ITtoAI member sees here, based on their verified skill profile. Sign in and complete your AI Readiness Assessment to see your own match.

MATCH SCORE FOR THIS ROLE

Based on verified skills against AI Application Engineer's required capabilities. A higher score reflects closer skill alignment — it does not guarantee an interview or offer.

Matched Skills

PythonRAGCloud

Skill Gaps

FastAPILLM APIs

RECOMMENDED PREPARATION

Focus on LLM API integration and production deployment patterns, then build practical evidence with a project like Production AI API. Revisit the relevant section of the AI Readiness Assessment to track progress.

Illustrative example. Match scores reflect assessed skill alignment — they do not guarantee an interview, offer or hiring outcome.

Job details

Overview

Nimbus Systems is looking for an AI Application Engineer to help embed large language model capability into its core product suite. You will work closely with backend and product teams to ship reliable, production-grade AI features — not just prototypes.

Responsibilities

  • Design and build LLM-powered features using retrieval-augmented generation and structured prompting.
  • Integrate third-party and open-source LLM APIs into existing backend services.
  • Own the reliability, latency and cost profile of AI features in production.
  • Collaborate with product and design on what AI capability should — and should not — do.
  • Write evaluation suites to catch regressions in model behaviour before release.

Required Skills

PythonFastAPIRAGLLM APIsCloud

Preferred Skills

Vector DatabasesAI EvaluationSystem Design

AI Technology Stack

PythonFastAPILangChainOpenAI APIPineconeDocker

Interview Process

What to expect

Application Review

Initial review of your profile, projects and assessed skills.

Technical Screen

A conversation covering LLM engineering fundamentals and past project work.

Practical Exercise

Build a small RAG-based feature against a provided dataset.

Team Interview

Meet the engineering team and discuss the practical exercise in depth.

Ready to take the next step?

Applying connects you with the ITtoAI team — your verified profile and assessed skills go with you.

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This is an example listing. Match scores and outcomes are illustrative and do not guarantee employment or hiring.