About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. 

Our responsibility is to ensure detect, protect, and prevent bad accounts from causing damage to Google users and products. We own the end-to-end solutions lifecycle—collecting, processing, and transforming massive, high-velocity data streams into the insights that powers multiple Google’s abuse-fighting systems.

In this role, you will contribute to the redesign and implementation of a next-generation data and semantic infrastructure designed to provide critical insights across the organization. Your work will involve identifying and resolving architectural bottlenecks to facilitate the business transition toward Agentic AI. We are seeking innovative problem solvers capable of transforming raw data into actionable business intelligence while partnering with cross-functional teams worldwide. 

Responsibilities

• Design and implement horizontally scalable systems specifically optimized for the unique constraints of account and device data.
• Architect and own the development of core components for signal ingestion and centralized repositories, ensuring data integrity and timeliness across the entire pipeline.
• Architect end-to-end data lifecycles to convert raw information into insights, overseeing the full range of collection, processing, and visualization of high-fidelity signals to empower organizational intelligence.
• Perform comprehensive performance analysis by executing advanced experiments to troubleshoot and enhance the efficiency of both individual nodes and large-scale distributed systems.
• Resolve system bottlenecks through the optimization of storage and processing architectures, while leveraging fleet metrics and custom tooling to monitor reliability and extract key performance data from operational workloads.