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.
Our team provides business system solutions to Supply Chain groups across Alphabet enabling plan, design, source, procure, build, transport, deliver and maintain machines, networks, data centers as well products within our Bets. We create solutions that solve problems at Google scale and optimize fulfillment across a complex global supply chain network. We leverage industry best practices and technologies and bring them together to create a delightful experience for our users.
As a Software Engineer, you will have an opportunity to grow your technical expertise, apply modern technologies, including Agentic AI and make significant contributions to the reliable and extensible platforms that power Google's future.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
****Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $211000 (USD) + 15% bonus target + bonus + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Design, develop, and maintain extensible platforms, leveraging technologies like Agentic AI, to optimize the design, planning, and deployment of Google's technical infrastructure.
- Write, test, and deploy high-quality, efficient code for services supporting critical hardware and supply chain operations, taking ownership of feature development.
- Collaborate with partner teams (e.g., Engineering, Operations, Product) to define requirements, influence solution design, and deliver technical solutions.
- Troubleshoot, debug, and resolve complex issues in existing codebases, ensuring system reliability and performance.
- Contribute to code reviews, documentation, and the continuous improvement of engineering best practices within the team.
Qualifications
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- Experience building and consuming APIs (e.g., REST, gRPC).
- Experience with database systems (e.g., Spanner, BigQuery, PostgreSQL).
- Experience deploying and managing applications on cloud infrastructure.
- Experience in the Java programming language.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience working on internal tools or enterprise systems and collaborating with internal stakeholders.
- Experience in multiple full system implementation life-cycles (e.g., analyze, design, build, test, implement, support).
- Experience developing accessible technologies.
- Familiarity with machine learning concepts and frameworks.