Design and implement scalable data infrastructure for AI agents, ensuring high-quality data delivery to institutional clients. Requires 3-6 years of experience in building performant data pipelines and ML systems, with expertise in AI-native environments and data quality.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
💻 Job Title: AI (Data) Engineer
💰 Salary: up to ~£120k + profit share
📈 Equity: 0.75 - 1%
📍 Location: Old Street (4-5 office days/week)
🔐 Company: Data processing AI Agents
👥 Team: ~5
💸 Funding: Pre-seed
About the company
This early stage start-up is processing hundreds of thousands of unstructured financial documents into clean, structured datasets for some of the world's largest financial institutions - producing the output of 50, with a team of 5.
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Forecasting £1.5m revenue within their first 12 months, they have an immense potential - not based on hype or inflated valuations, but rather achieving mega productivity through intelligent application of AI agents.
Their mid term goal is ~£50m revenue with a sub-30 person team. What's in it for you?
- Profit share. Cash in your account on regular basis - not a promise of a huge payout IF the company succeeds and sells.
About the role
You'll own data infrastructure end-to-end - ingestion, transformation, storage, delivery.
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The current agent system works. Your job is to scale it: more documents, more asset classes, more clients. You'll make architecture decisions, push the boundaries of agentic tooling and ship data as a product to institutional buyers who rely on it for decisions that move millions.
Full ownership from day one, with a genuine progression trajectory for the right person.
✅ Must have requirements:
- Roughly 3-6 years experience building performant data pipelines and ML systems in production
- Genuinely AI-native experience: Claude Code, Cursor or equivalent as your daily environment - not occasional experiments
- Python, Postgres, async, queues - fluent and battle-tested
- Experience in a small team (2-30 people) where you owned the whole function
- Data quality obsessive - inconsistencies bother you until they're fixed
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👍 Bonus points for:
- Experience at a financial data provider (Bloomberg, Refinitiv, Preqin, FactSet etc.) or quant finance
- Experience with LLMs in production / agentic workflow design
- Web scraping and document parsing at scale
🛂 VISA sponsorship is available if needed (but you need to be already living in the UK)
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