Company Spotlight
Cleo AI Jobs & Careers
Cleo is an AI-powered financial assistant — its entire product is a conversational AI interface that helps users manage their money. Founded in 2016 and now with 7M+ users primarily in the US and UK, Cleo represents one of the most AI-native fintech companies in Europe, where LLM and NLP engineering is at the heart of the product rather than supporting it.
Editorial content — ObiTech Jobs is not affiliated with Cleo.
What AI Is Cleo Building?
Cleo's product is AI — the entire user experience is a conversational interface in which users interact with an AI assistant (called Cleo) to understand their finances, get budgeting advice, build savings habits, and access credit products. This makes Cleo fundamentally different from banks that have AI as a back-office function: at Cleo, AI is the user interface.
Conversational AI and NLP — Cleo's core technical challenge is building a financial AI assistant that is genuinely helpful, accurate on financial information, and safe — it cannot give incorrect financial advice or misrepresent account data. The system combines LLMs for natural language understanding and generation with structured financial logic for calculations and account interactions. The LLM layer has evolved significantly with GPT-4 and Claude models replacing earlier custom NLU approaches.
Credit ML — Cleo has expanded into credit products (Cleo Cash Advance, Cleo Credit Builder). Credit decisioning draws on Cleo's rich behavioural data — how users interact with their finances through the Cleo interface provides signals for creditworthiness that traditional bureaus don't have.
Personalisation and financial behaviour ML — Cleo's effectiveness depends on understanding each user's financial patterns well enough to give relevant, timely advice. Spending categorisation, savings goal prediction, and personalised nudge timing are all ML problems.
Safety and evaluation — For an AI product in financial services, evaluation and safety are not afterthoughts. Cleo invests significantly in systems to evaluate whether AI-generated financial responses are accurate, appropriate, and compliant with FCA guidelines on financial promotions.
Roles Cleo Typically Hires For
LLM Engineer
Building and improving Cleo's conversational AI — prompt engineering, RAG, fine-tuning, evaluation, and productionising LLM applications in a financial context.
ML Engineer (Credit)
Credit decisioning models for Cleo's lending products. Behavioural ML, credit risk, fairness and explainability.
NLP Engineer
Financial entity extraction, intent recognition, spending categorisation, and personalised financial insight generation.
Data Scientist
Product analytics, personalisation, savings behaviour prediction, A/B testing of AI product changes.
AI Safety / Evaluation Engineer
Building evaluation frameworks for LLM responses — accuracy, safety, compliance, and user satisfaction metrics.
Culture & Interview Process
Cleo is a high-energy, product-focused startup — engineers here see their work directly in the product that millions of users interact with daily. The culture is collaborative and iterative; shipping fast and learning from user behaviour is core to how the team operates.
The interview process typically involves a take-home technical assessment focused on NLP or ML, a technical interview, and a conversation about how you approach ambiguous problems. Cleo values candidates who can combine technical rigour with product intuition — understanding that the goal is helping users with their finances, not just building technically impressive systems.
Cleo operates hybrid from London, with flexibility for experienced engineers. The team is relatively small by fintech standards, meaning engineers have significant influence on architectural decisions.
Quick Facts
2016
London, UK
7M+ (US & UK)
AI-native (conversational UI)
LLMs, NLP, credit ML, eval