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# Tech Lead Manager, Kubernetes AI Infrastructure

- **Company:** Google LLC
- **Location:** Kirkland, WA, United States
- **Experience:** Expert
- **Salary:** $207,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, C++ (Programming Language), Cloud Computing, Distributed Systems, Python (Programming Language), Machine Learning, Systems Development Life Cycle, Software Engineering, AI Infrastructure, Pytorch, Large Language Models, Deep Learning, Kubernetes, Information Technology, Slurm, Programming Languages
- **Published:** May 14, 2026
- **Apply:** https://seeker-sp.worksourcewa.com/jobview/GetJob.aspx?JobID=293414187

## About the Role

* Bachelor's degree, or equivalent practical experience.
 * 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
 * 3 years of experience in a technical leadership role.
 * 2 years of experience in a people management or team leadership role., * Master's degree or PhD in Computer Science, or a related technical field.
 * 8 years of experience leading, designing and implementing large-scale distributed systems.
 * 3 years of experience working in a complex, matrixed organization.
 * 2 years of experience with people management.
 * Experiences with deep learning frameworks (e.g., PyTorch, JAX), LLM applications and tools (e.g., SLURM, Ray).
 * Experience with machine learning infra (e.g., GPU, Cloud TPU, etc.).

## Description

* Design, guide and vet systems designs within the scope of the broader area, and write system development code to solve ambiguous problems.
 * Design, develop, and maintain Kubernetes-based systems to manage large-scale TPU infrastructure for on-premises and hybrid environments.
 * Oversee a team of software engineers specializing in distributed systems and AI infra, while fostering a high-performance and collaborative team environment.
 * Collaborate with major frontier AI Labs to influence the AI infrastructure roadmap and promote the use of TPUs for advanced ML workloads.
 * Work with cross-functional partners to deploy new infrastructure management tools that enhance Kubernetes' ability to handle large-scale GenAI tasks.


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