Senior Software Engineering Manager, AI/ML
- Sunnyvale, United States
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In most instances, this position requires in-person interviews as part of the hiring process.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees.
Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Kirkland, WA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience with software development.
- 5 years of experience in a technical leadership role.
- 5 years of experience in a people management or team leadership role.
- 5 years of experience with generative AI agents.
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.
About the job
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 must possess deep, frontier-level AI expertise and will be responsible for defining technical roadmap and accelerate Autonomous, Agentic development, AI-Engineering, and Agent Harness innovations to drive high-excellence execution across AutoCloud priorities. The role requires a leader who can drive substantial outcomes in the "Agentic era" by solving novel AI-specific problems at planet scale and establishing key platforms as authoritative systems within the Google Cloud ecosystem.
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: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
- Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
- Develop the long-term technical goal and roadmap within, and often beyond, the scope of your teams. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
- Oversee systems designs within the scope of the broader area, and review product or system development code to solve ambiguous problems.
- Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of solutions across multiple specialized ML areas.