Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.
For customers with hundreds of database instances across many projects and many database products, database center provides an organization-wide, cross-product unified fleet health platform, offering actionable insights and empowering customers to make informed optimization decisions. It integrates with multiple cloud databases (e.g., Cloud SQL, AlloyDB, Spanner, Bigtable, Memorystore, Firestore) and Google Cloud Platform (GCP) services (e.g., cloud resource manager, monarch, recommendations platform, security command center) to collect/aggregate the relevant health signals and powers a fleet health dashboard as well as Large Language Model (LLM) based conversational agent to enable customers to easily pinpoint issues and take corrective actions in their database fleet.
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.
Responsibilities
- Design and build centralized fleet management leveraging LLM and AI for database observability and manageability.
- Partner closely with team, Product Managers, UX and other Google Engineering teams to create, drive and deliver an innovative, compelling and user-friendly experience to our customers.
- Design, guide and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems.
- Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Improve the operational health of systems by identifying and implementing systemic improvements and partnering with engineering teams or customers to support database manageability.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience programming in C++, Java, Python, Kotlin or Go.
- Experience with large-scale distributed systems, API design, or test infrastructure.
Preferred qualifications:
- 6 years of experience with design and architecture, driving technical project strategy and testing/launching software products.
- 1 year of experience with AI/agentic tooling.
- Experience in data intelligence, analytics and AI/ML.
- Experience in observability, databases.
- Knowledge of observability constructs including distributed tracing, logging, and audit logging for AI applications.