I lead the engineering behind systems that catch invalid traffic and ad fraud before it costs publishers money — 10 million+ requests a day.
I manage a cross-functional team of five engineers building and scaling an AI-driven ad fraud detection system for web and mobile publishers.
My work spans productionizing ML models for invalid-traffic detection, designing Airflow pipelines for policy compliance, and researching publisher-side mobile IVT patterns — while running the 1:1s, reviews, and growth plans that keep the team moving. Before management, I spent five years shipping Android, iOS, and React Native products, and built an ad-monetization SDK from the ground up.
Leading a team of five scaling AI-driven ad fraud detection across 10M+ daily requests. Shipped pipeline features cutting client IVT rates by up to 50%, productionized ML models reducing mobile invalid traffic by up to 20%, and established mobile CI/CD and engineering practice across the org.
Foundational engineer for an in-house Android SDK for ad monetization and fraud detection: dynamic ad serving, a coroutine-driven analytics library on Kotlin Flow, a 50+ signal device-data collection system, and a GDPR-compliant consent module. Lifted performance ~15% and test coverage past 80%.
Integrated regional payments (M-PESA, Paymob) for SWVL — a unicorn with 10M+ downloads — supporting expansion across Africa and South America. Built a Bluetooth smart-grill companion app from scratch, a React Native crypto wallet, and iOS features for US clients, while training junior Android developers.
Maintained a US real-estate Android app — Stripe in-app purchases and custom geo-fenced Google Maps areas — and built features for a crime-reporting app with Firebase and Segment analytics, plus AppsFlyer and Dynamic Links for marketing attribution.
Open to conversations about ad fraud prevention, mobile engineering, and engineering leadership.