At the scale of 2.2 billion monthly users and 100 billion daily events, the attack surface isn't theoretical - it's the daily reality for Teads' security and engineering teams. The company operates a global omnichannel advertising platform, serving over 10,000 publishers and 20,000 advertisers across 36 countries. The core technical challenge is defending a system of massive, real-time data ingestion and predictive AI models that directly influence revenue for major publishers and brands.
The platform's infrastructure, built on cloud services and handling petabytes of event data, is where security work lives. Threats here involve securing high-throughput data pipelines, protecting proprietary machine learning models from manipulation, and ensuring the integrity of the ad-serving ecosystem. The technical domains - data science, cloud infrastructure, and advertising operations - are deeply intertwined, meaning security must be embedded at every layer, from creative delivery mechanisms to the predictive engines that determine outcomes.
Engineering and security operate with cross-functional autonomy, tackling problems in a high-velocity environment where the stakes are measured in both data integrity and direct financial impact. The culture signals around building reliable, scalable solutions and tackling ambiguous problems are backed by the concrete requirement to protect a platform where reliability and trust are non-negotiable currencies of the business.