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AI Engineer Northzone-backed fintech building AI global banks

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Jack & Jill
Full Time position
Listed on 2026-06-11
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: AI Engineer at $7M Northzone-backed fintech building AI for global banks
Location: Greater London

Job Title

AI Engineer

Location

London, UK

Company Description

$7M Northzone-backed fintech building AI-native automation for global banks

Job Description

You will own the AI and data infrastructure at the heart of an automation platform replacing $100B in manual bank processing. You'll build agentic systems and LLM pipelines using Lang Chain and Python, working directly with the world’s largest financial institutions to automate reasoning and complex decision-making workflows at scale.

Why this role is remarkable
  • Ship to production within your first sprint, building tools used by global giants like Worldpay, Barclaycard, and Nat West.
  • Backed by Northzone and Connect Ventures (investors in Spotify and Klarna), you'll join an elite team of ex-founders in a high-performance environment.
  • Direct influence on the product roadmap while reporting to the CEO and CTO, owning the AI quality bar for mission-critical banking systems.
What You Will Do
  • Build agentic workflows that automate reasoning, data analysis, and decision-making using Lang Chain, n8n, and Python.
  • Design and iterate on prompts and LLM integrations to drive reliable agent behavior across production financial systems.
  • Mine KYC/KYB signals from unstructured data to design pricing experiments and risk models for merchant onboarding.
The Ideal Candidate
  • AI-first engineer with hands-on experience in agentic frameworks like Lang Chain, Temporal, or n8n and prompt engineering.
  • Proficient in Python for modeling and ETL, with exposure to AWS data stacks including Glue, Athena, and Airbyte.
  • Strong stakeholder instincts with the ability to lead technical, data-driven conversations directly with banking partners and executives.
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