Job Description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with ML infrastructure or Generative AI Agents.
• 5 years of experience with Cloud platforms.
• 5 years of experience in developing large-scale distributed systems.
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• 3 years of experience with Kubernetes.

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.

Google Distributed Cloud (GDC) is a portfolio of fully managed hardware and software that brings Google Cloud’s infrastructure directly to the edge and customer data centers. Powered by Anthos, GDC is designed for high-performance local data processing and low-latency workloads. It particularly addresses organizations with strict requirements regarding data sovereignty, residency, and privacy. The Production Infrastructure team is at the forefront of building AI-native, agentic systems that drive efficient, scalable, and reliable operations.

In this role, you will design intelligent workflows that manage everything from AI-optimized hardware ordering to zero-touch deployments and turn-up processes across GDC's global fleet (both air-gapped and connected). The mission is to evolve traditional infrastructure management into a smart, self-managing platform powered by autonomous 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.

The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google

In this role, you will design intelligent workflows that manage everything from AI-optimized hardware ordering to zero-touch deployments and turn-up processes across GDC's global fleet (both air-gapped and connected). The mission is to evolve traditional infrastructure management into a smart, self-managing platform powered by autonomous AI agents.

Responsibilities

• Design the foundational architecture for massive, complex systems that span multiple Engineering teams or even different organizations.
• Defining the long-term technical roadmap (often 1-2 years out) and ensure the architecture can handle future scaling, performance, and reliability needs.
• Act as the technical bridge to ensure multiple teams are building cohesive components rather than disjointed, siloed products.
• Take technical ownership of massive, multi-quarter initiatives (from conception to deployment).
• Build a culture of psychological safety, rigorous engineering excellence, and "strong opinions, loosely held" across the wider engineering group and upskilling Tech Leads and Senior Engineers across the organization in prompt engineering, agent debugging, model evaluation, and AI-assisted coding practices.