Senior Software Engineer, AI Agent Ecosystem, ADK

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages (e.g., Kotlin, C++, Java).
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with data structures and algorithms.
• Experience developing accessible technologies.

About the job

Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. In this role, you aren’t just building technology; you’re shaping the frontier of enterprise and driving the evolution of advanced models.

We are dedicated to simplifying the creation, deployment, and management of production-grade AI agents. By building and supporting a comprehensive, open-source, multi-language ecosystem—highlighted by our agent development kit (ADK) and related agentic protocols we serve developers both inside and outside of Google. Our work is pivotal to forging a unified and powerful GenAI landscape for the entire developer community.

As a Senior Software Engineer, you will drive the technical goals, strategy, and architecture for the open-source components and tooling of our AI Agent ecosystem, including the agent development kit (ADK). You will lead the design and development of foundational libraries, SDKs, and developer tools, managing ambiguous and issues to enhance the end-to-end agent development lifecycle.
This role requires technical leadership to influence and collaborate with internal, external, and cloud platform teams, shaping the roadmap and ensuring seamless integration and deployment of AI agents.
You will be a key technical voice, mentoring engineers, setting standards for engineering excellence, and driving long-term investments to scale the platform and empower a vibrant developer community.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

As a Senior Software Engineer, you will drive the technical goals, strategy, and architecture for the open-source components and tooling of our AI Agent ecosystem, including the agent development kit (ADK). You will lead the design and development of foundational libraries, SDKs, and developer tools, managing ambiguous and issues to enhance the end-to-end agent development lifecycle.
This role requires technical leadership to influence and collaborate with internal, external, and cloud platform teams, shaping the roadmap and ensuring seamless integration and deployment of AI agents.
You will be a key technical voice, mentoring engineers, setting standards for engineering excellence, and driving long-term investments to scale the platform and empower a vibrant developer community.

Responsibilities

• Define and drive the architectural goals, technical strategy, and roadmap for foundational, scalable, and extensible open-source libraries and SDKs within the agent development kit (ADK) and related agentic protocols.
• Architect and lead the development of mission-critical tooling and infrastructure that improves the end-to-end AI agent development lifecycle (testing, debugging, deployment, observability), focusing on developer velocity, reliability, and scale.
• Provide technical leadership across the agent platform domain by managing the most ambiguous technical issues, mentoring junior engineers, advocating engineering excellence, and influencing technical direction through design reviews and setting team-wide standards.
• Identify and initiate long-term investments to reduce architectural complexity, improve system health, and unlock new capabilities for the AI agent ecosystem.