Job description

Within the Cloud AI organization, we focus on building highly differentiated, highly scalable, and easy-to-use products and services that enable our customers to transform their business with AI. Products such as Vertex AI and Gemini Enterprise comprise a portfolio that spans the needs of Developers, Data Scientists, Operation specialists in a broad range of industries. We not only provide customers with state-of-the-art models, such as Gemini, but also full Agent platforms and applications with strong security and governance. As the Senior Director of Cloud AI Safeguards Engineering you will lead the strategic direction, design, development, and operational execution of Safeguards for Cloud AI product portfolio. This role requires a technical leader who bridges complex AI engineering, state of the art Safeguards systems with disciplined business execution. The ideal applicant establishes strong engineering practices to navigate rapidly evolving products and adversaries, and builds flexible and scalable safety systems to handle the challenges. 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $364000 - $505000 (USD) + 40% bonus target + equity + benefits Learn more about benefits at Google . • Define and execute the technical strategy for the Cloud AI Safeguards engineering organization, ensuring alignment with broader Cloud AI products. • Setting a vision in AI, products, and safety systems, while navigating changes to model capability, usage across many products, and determined adversaries. Innovation is a key need to stay on the frontier of safety. • Maintain high standards for code quality, system reliability, and operational metrics in a fast-paced environment. Drive clarity via goals, roles, and responsibilities for your team and partner teams. • Oversee the architecture and deployment of secure, resilient, and multi-tenant cloud systems designed to sustain demanding AI workloads. • Recruit, retain, and develop a team of engineering leaders and technical contributors, establishing clear pathways for career growth and accountability. Set a culture of continuous improvement via feedback and self reflection within your team. • Bachelor’s degree in Computer Science or equivalent practical experience. • 20 years of professional experience in engineering leadership or related technical roles. • 10 years of experience in AI and machine learning, with a focus on developing and deploying AI-powered Safety systems. • Experience managing an engineering organization across multiple geographies and product portfolios. Minimum qualifications: • Bachelor’s degree in Computer Science or equivalent practical experience. • 20 years of professional experience in engineering leadership or related technical roles. • 10 years of experience in AI and machine learning, with a focus on developing and deploying AI-powered Safety systems. • Experience managing an engineering organization across multiple geographies and product portfolios. Preferred qualifications: • Master's degree in Computer Science or related field. • Experience building teams with excellent culture and developing leaders who have independently delivered impact. • Strong understanding of complex products, build threat models, and building system level safety. • Demonstrated ability to make risk based trade-offs. • Proven track record of successfully building defenses for complex platforms.

Requirements

Must-haves

The ideal applicant establishes strong engineering practices to navigate rapidly evolving products and adversaries, and builds flexible and scalable safety systems to handle the challenges.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Define and execute the technical strategy for the Cloud AI Safeguards engineering organization, ensuring alignment with broader Cloud AI products.
Setting a vision in AI, products, and safety systems, while navigating changes to model capability, usage across many products, and determined adversaries. Innovation is a key need to stay on the frontier of safety.
Maintain high standards for code quality, system reliability, and operational metrics in a fast-paced environment. Drive clarity via goals, roles, and responsibilities for your team and partner teams.
Oversee the architecture and deployment of secure, resilient, and multi-tenant cloud systems designed to sustain demanding AI workloads.
Bachelor’s degree in Computer Science or equivalent practical experience.
20 years of professional experience in engineering leadership or related technical roles.
10 years of experience in AI and machine learning, with a focus on developing and deploying AI-powered Safety systems.
Experience managing an engineering organization across multiple geographies and product portfolios.
Bachelor’s degree in Computer Science or equivalent practical experience.
20 years of professional experience in engineering leadership or related technical roles.
10 years of experience in AI and machine learning, with a focus on developing and deploying AI-powered Safety systems.
Experience managing an engineering organization across multiple geographies and product portfolios.

Nice-to-haves

US: $364000 - $505000 (USD) + 40% bonus target + equity + benefits
Master's degree in Computer Science or related field.
Experience building teams with excellent culture and developing leaders who have independently delivered impact.
Strong understanding of complex products, build threat models, and building system level safety.
Demonstrated ability to make risk based trade-offs.
Proven track record of successfully building defenses for complex platforms.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learning

Platform: google
Effort: medium

Benefits

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Vision