The role
From Google's own posting.
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 assume a critical leadership position overseeing a highly impactful, global organization of software engineers. You will define the strategic technical outlook to elevate the infrastructure, tools, and platforms we build for the global automotive industry and our Original Equipment Manufacturer (OEM) partners.
Drawing on your automotive industry expertise, you will navigate the unique requirements, quality standards, and integration patterns of deploying features for assisted and automated driving. You will be expected to set technical direction, influence across teams, and mentor other engineers, as well as be in creating and delivering impactful systems.
The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives.
The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.
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 .
Lead, manage, and scale a global engineering organization of approximately 15 software engineers, serving as a technical leader who manages overall team strategy and execution.
Refine and elevate engineering infrastructure for OEMs and the broader auto industry, ensuring tools and platforms meet rigorous safety, freshness, and accuracy standards for ADAS (Advanced Driver Assistance Systems) and Autonomous Driving features.
Drive the team's technical strategy for enhancing developer velocity across Geo Auto, overseeing critical validation pillars such as Drive Simulation for drive-focused capabilities.
Advocate the integration and development of Generative AI and Large Language Models into developer workflows to advance testing, automation, and debugging for complex auto ecosystems.
Partner with Geo Auto product leaders, GSDA global leadership, and external OEM partners to co-develop solutions, align multi-ecosystem initiatives, and advocate for technical capabilities.
Minimum qualifications:
Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
7 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
5 years of experience in a people management or team leadership role.
Experience with Machine Learning (ML), Generative AI, Reinforcement Learning, or Large Language Models (LLMs).
Preferred qualifications:
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
Experience in the automotive sector building infrastructure, developer tools, or platforms for OEMs, ADAS, or autonomous driving ecosystems.
Experience applying AI and machine learning to solve software development challenges (e.g., AI-powered testing, debugging, validation, or developer tooling).
Experience with simulation environments, A/B testing frameworks, or infrastructure for large-scale data processing.
Experience working in a complex, matrixed organization and collaborating with partner teams to co-develop solutions.
Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
7 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
5 years of experience in a people management or team leadership role.
Experience with Machine Learning (ML), Generative AI, Reinforcement Learning, or Large Language Models (LLMs).