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Tide is a fintech platform serving SMEs across the UK, India, Germany, and France with business banking and administrative solutions (invoicing, accounting). The company supports over 2 million members globally and has raised over $300 million in funding.
You will lead the engineering organization behind KYX (KYC and KYB), Tide's identity, onboarding, and continuous due diligence platform. This role unifies leadership across three domains: Onboarding KYX (identity, access, registration, due diligence policy execution, risk scoring, and agentic AI for applicant assessment), Continuous KYX (ongoing due diligence and team member onboarding), and Risk Scoring (ML models powering decisioning across both domains).
Key responsibilities include:
- Own engineering strategy and organization for KYX, unifying previously separate Onboarding and Continuous KYX lines
- Lead distributed engineering teams (backend, frontend, data science, ML) across Hyderabad, Delhi, Sofia, Belgrade, Bucharest, and Vilnius
- Own the KYX Scoring & ML capability end-to-end: model development, backtesting, staged rollout, and production monitoring
- Scale agentic AI in regulated workflows (onboarding risk scoring, screening, review, verification) within Tide's agentic governance framework
- Collaborate with KYX Ops, KYX Policy, Second Line of Defence, Product, and IAM teams across UK, EU, and India
- Deliver measurable outcomes: higher automated decisioning rates, improved due diligence quality, and reduced KYX cost per member
- Build once, deploy globally, keeping market-specific logic isolated
This is positioned as one of Tide's most important engineering roles, shaping member onboarding speed and quality, market expansion under Tide's own licenses, and applied AI advantage in a regulated environment.
Requirements:
- Experience leading engineering organizations in identity, onboarding, fraud, financial crime, or another regulated decisioning domain
- Strong track record turning platform investment into measurable outcomes: conversion, due diligence quality, unit economics, workflow automation
- Experience taking machine learning from development into production at scale and owning model performance post-launch
- Experience operating in regulated environments, working with Ops, Policy, and second line risk and compliance functions
- Strong judgment across organization design, delivery, platform strategy, data architecture, and technical quality
- Ability to lead distributed teams across multiple markets and unify previously separate engineering lines behind one roadmap
- Bonus: Experience deploying AI or agentic systems inside regulated workflows with clear governance, evaluation, and human oversight
