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Senior Software Engineering Manager, Geo Software Development Acceleration Team

Google
Seattle, USA
Senior · 8+ years experience
USD 262000-364000 / year
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Responsibilities

  • 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.
  • - 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.

Qualifications

  • 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.

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