Software Engineering Manager, Google Cloud TPU

• Build, mentor, and inspire a software engineering team. Cultivate a culture of high performance, innovation, psychological safety, and deliberate career development where every engineer grows.
• Shape the technical strategy and multi-year product roadmap, seamlessly aligning team objectives with the broader Google Cloud goal and our pioneering AI-first initiative.
• Drive engineering velocity across the entire project lifecycle, ensuring the predictable, high-quality delivery of scalable features.
• Drive deep technical decision-making for our infrastructure components, fostering a culture of code reviews, scalable architecture design, AI-first and data-driven development, while mentoring engineers.
• Advocate an unyielding customer-first mindset, establishing standards for service reliability, performance, and operational excellence, transforming complex customer requirements into technical realities, and maintaining a healthy production.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development, focusing on building distributed cloud services.
• 3 years of experience in an engineering management role, guiding software engineering teams, including hiring or team development.
• 2 years of experience in LLM training or inference, including performance optimizations, distributed execution, GPU or TPU acceleration, or PyTorch, JAX, or TensorFlow programming.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• 3 years of experience working in a complex, matrixed organization.

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development, focusing on building distributed cloud services.
• 3 years of experience in an engineering management role, guiding software engineering teams, including hiring or team development.
• 2 years of experience in LLM training or inference, including performance optimizations, distributed execution, GPU or TPU acceleration, or PyTorch, JAX, or TensorFlow programming.