Senior Director, AI-Driven SecOps & Cloud Security

Google; Washington (District of Columbia); On-site; USD 364,000 - 505,000; Full time

Benefits offered by this job

Health insurance

Retirement benefits (401k with company

Paid time off - 20 days/year

Sick time - 40 hours/year

Maternity leave - 28-30 weeks

Baby bonding leave - 18 weeks

Holidays - 13 paid days

Job summary

Google Cloud is seeking a SecOps engineering leader to scale our security product from 1,500 to 15,000 customers, delivering architecture resilient enough for global deployment and operational excellence across teams.

You will oversee the Agentic SOC initiative and drive the migration of our massive data footprint from F1/Spanner to BigQuery to unlock next-generation analytics and cost-efficiency across the organization.

Qualifications

• Bachelor's degree in CS or related field, or equivalent practical experience.
• 15 years of software development experience, with 5 years in technical leadership.
• Experience leading and managing a team of software engineers.
• Experience in AI/ML, platform development, distributed systems, or cybersecurity.
• Experience leading global organizations.

Responsibilities

• Define and execute long-term technical vision for Google SecOps.
• Build and lead a global engineering team.
• Partner with product management to ensure a security roadmap.
• Oversee migration from F1/Spanner to BigQuery with zero-downtime.
• Lead the Agentic SOC initiative integrating AI into analyst workflows.

Skills

Leadership experience

AI/ML

Platform development

Distributed systems

Cybersecurity

Global teams

Executive communication

Education

Bachelor's degree in Computer Science or related field

Tools

BigQuery

Job description

Google Cloud is seeking a SecOps engineering leader to scale our security product from 1,500 to 15,000 customers, delivering architecture resilient enough for global deployment and operational excellence across teams.

You will oversee the Agentic SOC initiative and drive the migration of our massive data footprint from F1/Spanner to BigQuery to unlock next-generation analytics and cost-efficiency across the organization.