Join a dynamic team shaping the future of search within Google Workspace. You'll lead engineering efforts to enhance how over a billion users find information across Gmail, Drive, Chat, and Calendar.

This role is pivotal in driving a strategic shift from traditional keyword matching to advanced AI-powered search. We are leveraging semantic retrieval, natural language understanding, and multi-modal search to redefine productivity and collaboration.

As a leader, you will influence the direction of workspace search, contributing to products like Gmail, Docs, and Drive. You'll be at the forefront of AI innovations, building the next generation of productivity tools and impacting billions of users globally.

Advocate for a culture of continuous improvement, overseeing system debugging, performance tuning, and technical debt management for robust production environments.

Collaborate with the Technical Lead to define and execute the technical roadmap, providing strong leadership for search and recommendation systems. Ensure end-to-end reliability and quality from data ingestion to serving.

Drive the development of advanced Information Retrieval and Machine Learning systems, including embedding-based search and natural language query understanding.

Establish and implement rigorous evaluation frameworks and success metrics, using offline/online evaluations and user feedback to enhance search relevance and satisfaction.

Foster a high-performing engineering culture through active coaching, performance feedback, and personalized career development for all team members.

A Bachelor's degree or equivalent practical experience is required.

We seek candidates with 8 years of experience managing and growing software engineering teams, focusing on performance management and career development. Additionally, 5 years in a people management or team leadership role is essential.

Experience in software engineering within Information Retrieval (IR), Natural Language Processing (NLP), or Machine Learning (ML) is crucial. Proven experience designing, implementing, and optimizing large-scale, high-performance, distributed search or quality systems in production is also necessary.