Software Engineering Manager II, Agentic AI Systems, Cloud Security

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.

Google Cloud Security is redefining security for the new AI era. Our goal is to deliver highly differentiated and Google-scale agentic defense to empower customers to defend their enterprises at machine scale and speed. Our team is at the forefront of revolutionizing the Google Security Operations (SecOps) through the power of artificial intelligence. This is a unique opportunity to lead a team of talented engineers in building the next generation of Security Agentic AI systems that will protect major organizations worldwide.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
  
• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• 2 years of experience with state of the art GenAI technologies (e.g., Large Language Models (LLMs), Agentic development etc.).
• Experience in Security domains.