AI Engineer

AI EngineerLondon (SE1) | Hybrid – 3 days on-site | £80,000 – £90,000 DOE + 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 doTake AI and ML systems from ideation to productionBuild GenAI applications with LLMs and orchestration frameworks, evaluation, safety and cost built inWrite clean, production grade Python for cloud native environmentsApply CI/CD, containerisation, monitoring and observability as standardMonitor live models for drift, bias and degradation, and act on itBuild reusable components that speed up the next projectTranslate business problems into AI solutions, and explain them to non-technical stakeholdersMinimum technical requirements – Important – please read before applyingPython — 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 infrastructureMLOps — CI/CD, containerisation, monitoring, evaluation frameworks.Data at scale — large, complex datasets and robust pipelines for training, fine-tuning and inference.Not for: Candidates who haven't owned deployment and can give clear evidence of thisPackage£80,000 – £90,000 DOE£5,000 cash car allowanceSingle-cover private medical3 days on-site, London. Monday is team day; the other two are flexible. Relaxed over August and Christmas–New Year.Process30 mins, Teams Head of AI Engineering. Walk through an ML /AI project you took full lifecycle. Expect it probed properly.90 mins, Teams 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. Greenfield problems, short paths to production, visible impact .Fast paced environment within inside a large business with the stability and data to match.Apply here, or message me for a confidential conversation.justin.toomey@datatech.org.uk