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Senior Software Engineering Manager, AI/ML at Google, San Francisco, CA

Senior Software Engineering Manager, AI/ML at Google in San Francisco, CA. $262,000 to $364,000 a year. Apply with swipeandhired.

Lead, mentor, and grow a high-performing team of engineers focused on developing and deploying next-generation agentic AI for security that will power the Google's Agentic SecOps offering.

Drive the technical goal and strategy for the security harness ensuring alignment with the broader security teams.

Collaborate with cross-functional engineering teams along with 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 to 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 the latest advancements in AI, machine learning, and cybersecurity.

Minimum qualifications:

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 (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

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 in a technical leadership role.

5 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.

5 years of experience working in a complex, matrixed organization.

Experience in 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.

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 shape the technical goal and strategy, drive rapid and agile execution, and foster a culture of innovation, experimentation and uncompromising quality. Your leadership will ensure Google Unified Security and Threat Operations (GUSTO) AI becomes a leading agentic platform for the next wave of AI-driven cybersecurity solutions.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google .
In most instances, this position requires in-person interviews as part of the hiring process.

Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

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 (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

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 in a technical leadership role.

5 years of experience in a people management, or team leadership role.