Software Engineer Iii, Full Stack, AI Development Tools

Google Google · Big Tech · Warsaw, Poland

Software Engineer III role focused on developing GenAI and Vertex-based development tools, including server and middleware code that interacts with LLMs. The role involves integrating next-generation LLMs with a focus on performance and deployment constraints, working closely with AI researchers and product managers.

What you'd actually do

  1. Design, develop, test, deploy, maintain, and enhance software solutions.
  2. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
  3. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  4. Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  5. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

Skills

Required

  • software development in one or more programming languages
  • full stack development
  • back-end such as Java, Python, Golang, or C++ codebases
  • front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent
  • google cloud platform
  • enterprise software architecture

Nice to have

  • Generative AI
  • Performance Optimization
  • Go
  • data structures and algorithms
  • accessible technologies

What the JD emphasized

  • develop GenAI and Vertex-based development tools
  • develop server code as well as middleware code which implement functionalities that interact with Google's latest Large Language Models
  • develop features that integrate the next-generation large language model with a balanced trade-off between performance and deployment constraints

Other signals

  • develop GenAI and Vertex-based development tools
  • develop server code as well as middleware code which implement functionalities that interact with Google's latest Large Language Models
  • develop features that integrate the next-generation large language model with a balanced trade-off between performance and deployment constraints