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Tide is a fintech platform serving over 2 million SMEs globally with business banking and administrative solutions including invoicing and accounting. The company has raised over $300 million and operates across the UK, India, Germany, and France with 2,800+ employees.
You will lead the engineering organization behind KYX (KYC and KYB), Tide's identity verification, onboarding, and continuous due diligence platform. This role unifies engineering leadership across three domains: Onboarding KYX (identity, access, registration, due diligence policy execution, and risk scoring), Continuous KYX (ongoing due diligence and team member onboarding), and Risk Scoring (ML models powering decisioning across both domains).
You will own engineering strategy and organization, leading backend, frontend, data science, and ML engineering teams distributed across Hyderabad, Delhi, Sofia, Belgrade, Bucharest, and Vilnius. Key responsibilities include:
- Develop and execute KYX engineering strategy, unifying previously separate Onboarding and Continuous KYX lines
- Lead the KYX Scoring & ML team as a shared capability serving both onboarding and ongoing decisioning, owning the full model lifecycle from development through backtesting, staged rollout, and production monitoring
- Scale agentic AI in regulated workflows (onboarding risk scoring, screening, review, verification) in line with 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 and screening quality, and reduced KYX cost per member
- Build once, deploy globally, keeping market-specific logic isolated
This role sits at the intersection of regulated risk operations, member-facing conversion, and applied AI. You will shape how quickly and well Tide onboards members, how confidently the company scales into new markets under its own licenses, and how applied AI compounds into lasting competitive advantage in a regulated environment.
Requirements:
- Experience leading engineering organizations in identity, onboarding, fraud, financial crime, or another regulated decisioning domain
- Strong track record of turning platform investment into measurable outcomes: conversion, due diligence quality, unit economics, and workflow automation
- Experience taking machine learning from development into production at scale and owning model performance once live
- Experience operating in a regulated environment, 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
