Engineering Manager - Workspace Search Quality

About The Role

This is a leadership opportunity at Google managing engineering teams focused on Workspace Search Quality products like Gmail, Drive, Chat, and Calendar. The role involves guiding the development of advanced search technologies and AI-driven relevance improvements to serve over a billion users globally. The manager oversees multiple teams, influences product strategy, and collaborates cross-functionally to innovate next-generation search capabilities.

Key Responsibilities

• Cultivate a data-driven work environment to continuously enhance search systems through debugging, performance tuning, and addressing technical debt for stable production operations.
• Collaborate with Technical Leads to establish and execute a technical vision and roadmap ensuring end-to-end reliability and excellence in search and recommendation systems.
• Lead efforts in developing advanced Information Retrieval and Machine Learning models, including embedding-based retrieval, ranking algorithms, and natural language query understanding.
• Set up comprehensive evaluation frameworks and success metrics leveraging offline/online testing and user feedback to measure and improve search quality and user satisfaction.
• Promote a culture of engineering excellence by coaching, giving performance feedback, and supporting career advancement across the team.

Minimum Qualifications

• Bachelor’s degree or equivalent practical experience.
• At least 8 years managing and growing software engineering teams with experience in performance management and career development.
• Minimum 5 years in people management, supervision, or team leadership roles.
• Software engineering background in Information Retrieval, Natural Language Processing, or Machine Learning.
• Proven experience designing, building, and optimizing distributed, large-scale, high-performance search or quality systems in production.

Preferred Qualifications

• Master’s or PhD in Computer Science, Machine Learning, NLP, Information Retrieval, or related field preferred.
• Familiarity with embedding-based retrieval (EBR), vector search, query natural language understanding (qNLU), and large language models (LLMs) applied to search/recommendation.
• Experience improving system latency and scalability.
• Understanding of advanced architectures including agentic systems, tool-calling, and Retrieval-Augmented Generation (RAG) grounding layers.
• Exceptional communication and collaboration skills with demonstrated ability to align cross-functional stakeholders and manage competing priorities.

Additional Information

Google is an equal opportunity employer committed to diversity and inclusion, welcoming applicants regardless of race, gender, age, sexual orientation, disability, or veteran status. Accommodations are available upon request during the application process.