Senior Software Engineering Manager, AI/ML

Google•San Francisco, CA

7h•$262,000 - $364,000

About The Position

As a Software Engineering Manager, you provide technical leadership for major projects while managing a team of engineers. You manage project goals, contribute to product strategy, and develop your team. The role involves managing engineers across multiple teams and locations, a large product budget, and deployment of large-scale projects across multiple international sites. In this role, you will shape technical goals and strategy, drive rapid and agile execution, and foster a culture of innovation, experimentation, and uncompromising quality. You will lead work to make Google Unified Security and Threat Operations (GUSTO) AI a leading agentic platform for AI-driven cybersecurity solutions.

Requirements

Bachelor’s degree or equivalent practical experience.
8 years of experience with software development.
7 years of experience leading technical project strategy, ML design, and optimizing end-to-end machine learning, such as model deployment, model evaluation, data processing, debugging, and fine-tuning.
5 years of experience in one or more of the following: speech/audio, reinforcement learning, ML infrastructure, or specialization in another ML field.
5 years of experience in a technical leadership role.
5 years of experience in a people management or team leadership role.

Nice To Haves

Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
5 years of experience working in a complex, matrixed organization.
Experience building and deploying Agentic AI systems.
Experience in highly scalable and available distributed systems, cloud services, or data platforms.
Understanding of security-related areas.
Excellent action and execution skills.

Responsibilities

Lead, mentor, and grow a high-performing team of engineers focused on developing and deploying next-generation agentic AI for security to power Google's Agentic SecOps offering.
Drive the technical goal and strategy for the security harness, ensuring alignment with broader security teams.
Collaborate with cross-functional engineering teams, product management, data science, and security engineering to define product requirements and roadmaps and deliver high-impact features.
Oversee the end-to-end development lifecycle, from ideation and design through implementation, testing, and deployment of robust and scalable AI-driven agentic security solutions.
Foster a culture of innovation, excellence, and continuous improvement, staying abreast of advancements in AI, machine learning, and cybersecurity.