Qualifications

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience in software development and with data structures/algorithms.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
  
• Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, natural language processing or other ML discipline.
  
• Experience in Generative AI (e.g., Language Models, Multi-Modal, Vision Models).
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
  

Summary

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience in software development and with data structures/algorithms.
  
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
  
• Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, natural language processing or other ML discipline.
  
• Experience in Generative AI (e.g., Language Models, Multi-Modal, Vision Models).
  

Description

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.

Google Cloud Platform (GCP) Networking is global in nature, and our customers design, configure, maintain and operate large complex deployments. Our team is responsible for building AI assisted troubleshooting solutions as part of Gemini Cloud Assist, catering to GCP customers as well as internal support teams to understand users intent, perform root cause analysis and provide quality insights. In this role you will join a team that defines a troubleshooting platform not just for GCP networking but for entire GCP product portfolio.

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.

Responsibilities

• Work as an AI SWE, individual contributor and leader on Gemini Cloud Assist Troubleshooting team.
• Work with Support and Support Platform leadership, Product, and Engineering teams to enable insights and data-driven decision making for driving Gemini Cloud Assist Troubleshooting quality for cloud customers.
• Work with Support and playbook data to perform end-to-end analysis.Identify the most important business problems, translating these to tractable questions, processing data and performing analysis, and then communicating the results to stakeholders to inform the product direction.
• Interact cross-functionally and cultivate strong partnerships with a wide variety of teams. Work closely with Engineering, Product, Design, Operations, and User Research to identify opportunities for impactful analysis.