Engineering Director, Autonomous Cloud

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

The AI space is evolving rapidly with newer and powerful models, agent frameworks, protocols, and security. We are imagining a cloud that configures, optimizes, and secures itself without human intervention. The Autonomous Cloud represents the next generation of computing where the cloud doesn’t just host data and applications but also manages and improves itself in real time.

In this role, you will utilize frontier-level AI expertise and will be responsible for partnering with the Product Lead and Uber Tech Lead to define technical strategy and accelerate Autonomous, Agentic development, AI-Engineering, and Agent Harness innovations to drive execution across AutoCloud priorities.

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.

Responsibilities

• Partner with the Product Manager Lead and Uber Tech Lead to define the Autonomous Cloud technical strategy and accelerate Autonomous Agentic development, AI-Engineering, and Agent Harness innovations.
• Oversee the integration of Agent Platforms and manage the expansion of Autonomous agent lifecycles and experiences.
• Establish the eval harness as the authoritative quality gate and drive the transition of the organization to an eval-first environment by hill climbing, challenging evals to Gemini models.
• Work with and influence stakeholders across the organization to build joint roadmaps and drive adoption of Autonomous Cloud.
• Partner closely with Cloud AI and Google Deepmind (GDM) to production-ize GDM research and scale Autonomous and Agentic Development across first-party AutoCloud producers with unified agentic and eval frameworks and tooling.

Minimum qualifications:

• PhD in Computer Science, Mathematics, or other relevant engineering discipline or equivalent practical experience.
• 15 years of software engineering experience building and working with large-scale systems in a technology organization.
• 5 years of experience leading frontier-level AI, AI-Engineering, Agentic Engineering, Applied AI solutions and ML-related technologies to solve real-world AI/ML problems in consumer or enterprise applications.
• 5 years of experience as a Software Engineering leader in ML Infrastructure, ML or AI for products, or related fields.
• Experience with technical innovation within cross-functional engineering environments.
• Experience leading engineering teams through organizational and technical transformations.

Preferred qualifications:

• Experience managing complex cross-functional dependencies with research groups and cloud platform teams.
• Experience successfully producing software products and large-scale distributed systems.
• Experience in configuration management tools and automation efforts with technical troubleshooting and performance tuning experience with Enterprise or Data Center Network architecture.
• Expertise in building and scaling autonomous agent frameworks or cloud automation infrastructure at planet scale.
• Expertise building Gen AI, ML products, Agent frameworks, Agent protocols (e.g., MCP, A2A), RAG, Prompt Engineering, Evals, etc.