Software Engineer Manager II, Embedded Systems/Firmware

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree, or equivalent practical experience.
• 8 years of experience in software development.
• 3 years of experience with embedded operating systems.
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.
• Experience with embedded systems and Linux.

PREFERRED QUALIFICATIONS:

• Master's degree or PhD in Computer Science, or related technical field.
• 3 years of experience working in a complex, matrixed organization.
• Experience with ARM, Diagnostics, Networking, Servers, Linux Internals.

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.

As an Engineering Manager, you will lead software engineers developing embedded

software, diagnostic tests, and tools to validate custom SoCs, servers, and

SmartNICs. You will optimize system health, test performance, and solve

reliability problems for millions of machines across global data centers. You

will drive hardware quality decisions on designs, working on projects that push

technology limits.

Your team will support critical infrastructure for machine learning, search,

security, and video processing, giving you an unmatched opportunity to make a

massive, global impact.

The AI and Infrastructure team is redefining what’s possible. We empower Google

customers with breakthrough capabilities and insights by delivering AI and

Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our

customers include Googlers, Google Cloud customers, and billions of Google users

worldwide.

We're the driving channel behind Google's groundbreaking innovations, empowering

the development of our cutting-edge AI models, delivering unparalleled computing

power to global services, and providing the essential platforms that enable

developers to build the future. From software to hardware our teams are shaping

the future of world-leading hyperscale computing, with key teams working on the

development of our TPUs, Vertex AI for Google Cloud, Google Global Networking,

Data Center operations, systems research, and much more.

Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• Manage, mentor, and grow a team of software engineers, fostering a culture of

technical excellence and collaboration. Provide regular coaching, performance

feedback, and support for career development.

• Drive the technical goal and roadmap for software, automation, and

diagnostics used in machine management, health testing, and life-cycle

management.

• Lead your team's efforts in the New Product Introduction process. Ensure all

newly turned up hardware is validated, properly configured, and performing as

expected without defects.

• Provide technical guidance and remain available in key areas, including

system design, code reviews, and complex problem-solving.

• Drive the development of data insights and analytics to understand complex

result sets from diagnostics.