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Senior Software Engineer, App and Ecosystem Trust

Google
4 days ago
Full-time
On-site
Bengaluru, Karnataka, India
Engineer

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages.
  • 3 years of experience with full stack development, across back-end such as Java, Python, Golang, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.
  • 3 years of experience testing, maintaining, or launching software products.
  • 1 year of experience with software design and architecture.

Preferred qualifications:

  • Master's degree or PhD in Computer Science, or a related technical field.
  • 5 years of experience with data structures and algorithms.
  • 1 year of experience in a technical leadership role.
  • Experience in server platform and Java apps framework.
  • Experience in productionization, monitoring, and releasing an infrastructure platform.
  • Experience in spanner database.

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.

App and Ecosystem Trust (AET ) Platforms team is building a new generation of common workflow, decisioning and storage infrastructure platforms for Android app and ecosystem safety, which the entire Android and Play Trust and Safety stack will be implemented on top of that platform (ML detection of abusive apps/developers, review and enforcement workflows). Thus the team plays a central role for app safety and this position presents a lot of room for growth. Our infrastructure helps protect Android users by serving app reviews per year.

In this role, you will leverage your expertise in Google Infrastructure to help us grow and scale our decisioning and storage infrastructure.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

Responsibilities:

  • Build distributed systems to help identify and stop abusive apps and developers. Be responsible for building full stack infrastructures and services to improve developer experience and operational efficiency for Play and Android.
  • Design, develop and deploy scalable infrastructure for workflow configuration, decisioning and storage, support cross-team integration within AET between binary static and dynamic analysis, ML model, human review, and communication to Play developers.
  • Design and develop user friendly tools to visualize workflow dependency graphs and track the execution state of each entity within the engine. Identify and solve technical problems while making a direct impact on the safety of the Android ecosystem.
  • Design and develop the front-end review platform for AET team.
  • Work with other App Safety teams to deliver impact (supporting product impacting policy launches, improve the feedback loop to our ML system).