AI/ML Software Engineer Manager II, Storage Search at Google

About the job

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

In this role, you will focus on Semantic Search, Object Context, and related features for Google Cloud Storage (GCS) which are critical for the GCS semantic storage and actions charter. The team is critical in building the capability to analyze unstructured data, discerning its meaning, context, and relationships into a knowledge graph.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Partner with Product Managers (PMs) and Technical Leads (TLs) to define the technical roadmap and design the core architecture, ensuring the reliability and evolution of Google's foundational storage infrastructure.

• Lead delivery of AI experiences (e.g., object context or semantic search), driving execution, accuracy, and consistency for critical user-facing features.

• Establish the team's future technical direction, leverage GCS architecture knowledge, and provide technical guidance to the team.

• Manage a team of software engineers, overseeing project execution across user-facing features, performance, and distributed systems.

• Build and maintain a safe and effective team environment, coaching and mentoring engineers for continuous career development and growth.

Minimum qualifications

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development.

• 5 years of experience working on high-scale distributed storage (e.g., cloud storage, object stores).

• 3 years of experience in a technical leadership role.

• 2 years of experience in a people management or team leadership role.

• 2 years of experience with modern search technologies, information retrieval systems, or developing AI/ML-driven features, related to semantic search, indexing, or context-aware data retrieval.

Preferred qualifications

• Master's degree or PhD in Computer Science or related technical field.

• 3 years of experience working in a changing organization.

• Experience with modern database technologies (e.g., NoSQL or relational) for managing metadata and structured storage data.

• Experience in building search infrastructure, indexing pipelines, or high-performance query execution systems.