About the role
Own the engineering strategy and execution for Ads Quality systems across signal processing, entity systems, model execution, decisioning, feedback, and measurement. Build scalable real-time, nearline, and offline systems supporting very large volumes and demanding reliability requirements. Create the production infrastructure that allows new models and signals to move rapidly from experimentation into safe global deployment. Partner with Applied Science on model integration, evaluation, experimentation, serving trade-offs, and productionization. Build common engineering foundations for heterogeneous AI workloads including classifiers, multimodal models, LLMs, agents, and deterministic systems. Develop feedback, observability, experimentation, and diagnostic systems that make quality problems easy to find and fast to fix. Drive architectural simplification and prevent the quality stack from becoming a collection of bespoke pipelines and one-off services. Lead and grow senior engineers, engineering managers, and technical leaders capable of independently owning complex areas. Drive difficult programs across organizational boundaries and maintain a high bar for architecture, engineering quality, and production ownership. 15+ years of software engineering experience, or equivalent technical depth. Significant experience leading senior engineers, engineering managers, or large engineering organizations. Strong technical depth in distributed systems, AI/ML infrastructure, decision systems, or large-scale data platforms. Experience building production systems that operationalize machine-learning models at significant scale. Strong judgment around latency, throughput, reliability, freshness, cost, observability, and operational safety. Ability to challenge architecture, understand failure modes