Staff Software Engineer, AI Transformation Lead

About the role

MINIMUM QUALIFICATIONS:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience programming in C++, Java, Python, Kotlin or Go.
• 5 years of experience testing, and launching software products.

• 3 years of experience with software design and architecture.
• Experience integrating generative AI tools or LLM interfaces into workflows.

PREFERRED QUALIFICATIONS:

• Bachelor's degree in Computer Science, a related technical field, or

equivalent practical experience.

• Experience in Software Development Kit (SDK) or developer framework

development in one or more modern programming language (e.g., Python, Go,

Java, TypeScript).

• Experience architecting system automation, code generation pipelines, or

complex software algorithms.

• Experience integrating Generative AI, Large Language Models (LLMs), or

autonomous AI agents into software engineering workflows.

ABOUT THE JOB:

Google's software engineers develop the next-generation technologies that change

how billions of users connect, explore, and interact with information and one

another. Our products need to handle information at massive scale, and extend

well beyond web search. We're looking for engineers who bring fresh ideas from

all areas, including information retrieval, distributed computing, large-scale

system design, networking and data storage, security, artificial intelligence,

natural language processing, UI design and mobile; the list goes on and is

growing every day. As a software engineer, you will work on a specific project

critical to Google’s needs with opportunities to switch teams and projects as

you and our fast-paced business grow and evolve. We need our engineers to be

versatile, display leadership qualities and be enthusiastic to take on new

problems across the full-stack as we continue to push technology forward.

As an AI Transformation Lead for Cloud SDK Client Libraries, you will own the

technical strategy, scoping, and outcomes for shaping our product to work

seamlessly with AI coding agents and driving internal engineering workflows.

While your core focus is on AI transformation, you will also take leadership in

advancing Cloud SDK and Client Libraries overall beyond the AI transformation

scope. You will manage large, ambiguous challenges, driving technical vision

across multiple language ecosystems (Python, Java, Go, Node.js, etc.).

Partnering with Client Libraries Engineering Managers (EMs), you will identify

hidden opportunities to optimize SDK development and empower our engineers to

code effectively alongside AI agents.

Google Cloud accelerates every organization’s ability to digitally transform its

business and industry. We deliver enterprise-grade solutions that leverage

Google’s cutting-edge technology, and tools that help developers build more

sustainably. Customers in more than 200 countries and territories turn to Google

Cloud as their trusted partner to enable growth and solve their most critical

business problems.

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:

• Define and drive the AI transformation strategy for Cloud SDK Client

Libraries, improving both external-facing Client Library capabilities and

internal development pipelines.

• Collaborate cross-functionally with Client Libraries EMs and stakeholders to

align roadmaps, reduce engineering toil, and standardize AI tooling adoption.

• Architect and implement scalable, maintainable SDK features and codegen

automation utilizing AI agents and Large Language Models (LLMs).

• Provide technical mentorship to engineers, establishing best practices for

hybrid development (humans working alongside AI agents).

• Define and monitor quantifiable measures of quality, reliability, and

productivity for AI-driven workflows.