Minimum qualifications: Bachelor’s degree, or equivalent practical experience. 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript). 3 years of experience with data structures or algorithms and software development in one or more programming languages. 3 years of experience in a technical leadership role. 2 years of experience in a people management or team leadership role. Preferred qualifications: Master's degree or PhD in Computer Science or related technical field. 3 years of experience working in a complex, matrixed organization. Experience with backend development in one or more of the following: C++, Go, Java, or gRPC. Experience with observability, large-scale distributed systems or planetary-scale data systems. Experience with Site Reliability Engineering (SRE), managing high-availability service infrastructure, and on-call support rotations. About the job 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. As a part of Cloud Observability, which empowers Google Cloud Platform (GCP) customers through their AI transformation by providing a high-performance platform for enterprise applications and AI workloads, the Cloud Metrics Platform team provides the public-facing APIs essential for cloud monitoring. You will enable users to gain deep insights into system health and performance, generate real-time alerts, and maximize availability at scale. You will act as a critical bridge between Google's planetary-scale internal monitoring systems and public cloud services, the team partners across GCP to deliver a compelling, end-to-end observability experience.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s 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 - $301000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Set and communicate team priorities that support the broader organization's goals, aligning strategy, processes, and decision-making across teams. Establish clear expectations with individuals based on their level and role and aligned to the broader organization's goals, while meeting regularly with individuals to discuss performance and development and provide feedback and coaching. Develop the mid-term technical goal and roadmap within the scope of your (often multiple) team(s), evolving the roadmap to meet anticipated future requirements and infrastructure needs. 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).