AI EngineerLondon ( SE1) | Hybrid
Apply now, read the job details by scrolling down Double check you have the necessary skills before sending an application.
- 3 days on-site | 80,000
- 90,000 DOE + 5,000 car allowance + private medicalThe opportunityA prestigious household name UK consumer services business with tens of millions of operational events a year.
They invested in and built a central AI function twelve months ago.
It's now 15 strong across Data Science, Data Engineering, Product and AI Engineering, and growing!Squad model: DS, DE, Product and AI Engineering form around a problem and own the product end to end.
No throwing models over a wall.What you'll do• Take AI and ML systems from ideation to production• Build GenAI applications with LLMs and orchestration frameworks, evaluation, safety and cost built in• Write clean, production grade Python for cloud native environments• Apply CI/CD, containerisation, monitoring and observability as standard• Monitor live models for drift, bias and degradation, and act on it• Build reusable components that speed up the next project• Translate business problems into AI solutions, and explain them to non-technical stakeholdersMinimum technical requirements
- Important
- please read before applying• Python
- strong and production-grade.
There's a live coding exercise at interview.• ML, full lifecycle
- framing through training, deployment, monitoring and retraining.
In production, not in a notebook.• GenAI / LLMs
- applications built with LLMs and orchestration frameworks, shipped to real users.• Azure & Databricks
- not expert level, similar can work but someone who has clear experience with cloud infrastructure• MLOps
- CI/CD, containerisation, monitoring, evaluation frameworks.• Data at scale
- large, complex datasets and robust pipelines for training, fine-tuning and inference.Not for: solution architects, software engineers without applied AI, data scientists who haven't owned deployment, or anyone whose GenAI stops at prompt engineering.Package•80,000
- 90,000 DOE•5,000 cash car allowance• Single-cover private medical• 3 days on-site, London.
Monday is team day; the other two are flexible.
Relaxed over August and Christmas-New Year.Interview Process30 mins, Teams
- Head of AI Engineering.
Walk through an ML project you took full lifecycle.
Expect it probed properly.90 mins, Teams
- the two current AI Engineers.
Live Python and problem-solving, then a deep dive on your wider skill set.In person
- culture and commercial fit with the Head of AI Engineering and Director of AI.The WhyNew function, so expect ambiguity and pace. xsabvtc
Greenfield problems, short paths to production, visible impact .Working inside a large business with the stability and data to match.Apply here, or message me for a confidential
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