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Contract AI Engineer — Generative AI & Agentic Systems
3 months · Day rate (negotiable) · Remote, UK-based
A boutique AI and cyber advisory consultancy needs a strong hands-on engineer to add technical depth across a run of financial-services engagements — taking clients from "should we use GenAI?" to systems that actually ship inside regulated environments.
You'd work alongside the lead consultant, who owns the client relationship and quality. Your job is the engineering: shaping the technical recommendations, then helping build them — agentic workflows, RAG pipelines, and the identity, data and governance plumbing that makes AI safe to run inside a bank.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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.
This is production work, not proofs of concept. We want someone who's put LLM and agentic systems into real, regulated settings and can explain them in plain English to people who don't write code.
You'll likely bring:
- Production experience with LLM / agentic systems — LangGraph, LangChain, LlamaIndex or similar — and solid MLOps/LLMOps fundamentals
- Fluency in regulated or enterprise data environments: identity, data architecture, governance
- A security instinct — you think about risk, not just capability
- The judgement to advise, not only implement


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