AI Cloud Enablement Engineer

Role & responsibilities

• Platform Availability: Ensure that the AI Platform (Vertex AI) is available and functioning as expected.
• Security: Ensure that public models are exposed securely and that the platform follows industry best practices for security and governance.
• User Support: Provide support and enablement to other teams, helping them to work within the platform in a secure and repeatable pattern.
• Establish Reusable Patterns: Develop reusable patterns to be used across engineering teams, ensuring consistency and efficiency and apply these patterns to AI and ML workflows.
• Collaborate: Work closely with various business and technology teams to create a clear and cohesive vision for the future state of our Google Cloud Platform.
• Stay Informed: Maintain awareness of industry trends and technologies, recommending timely adjustments to strategies as appropriate and stay up to date on AI and ML advancements.
• Onboarding & Enablement: Support teams with onboarding and enablement, including building onboarding materials and providing training.
• Troubleshooting Workflows: Address training failures, endpoint errors, and other issues that arise.
• Incident Management: Manage incidents specific to Vertex AI and ensure timely resolution.