Datatech Analytics
AI Engineer
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AI Engineer
London (SE1) | Hybrid – 3 days on-site | £80,000 – £90,000 DOE + car allowance + private medical
The Opportunity
A 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 stakeholders
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Minimum 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: Candidates who haven't owned deployment and can give clear evidence of this
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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.
Process
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30 mins, Teams Head of AI Engineering. Walk through an ML /AI project you took full lifecycle. Expect it probed properly.
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90 mins, Teams Live Python and problem-solving, then a deep dive on your wider skill set.
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In person Culture and commercial fit with the Head of AI Engineering and Director of AI.
The Why
New 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.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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