GCP Cloud Enablement Engineer

Job description

As an AI Cloud Enablement Engineer, you will play a crucial role in ensuring that the AI Platform (Vertex AI) is available, secure, and functioning as expected. You will be responsible for creating a user-friendly platform that enables other teams to work within it in a secure and repeatable pattern using zero-touch automation for AI workloads. - **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. **Technical Experience and Qualifications:** - Relevant work experience in cloud engineering. - **AI Platforms:** Understanding of AI platforms in a cloud environment (Vertex AI, CoPilot, Sagemaker, Bedrock). - **Cloud Platform:** Proficiency in Cloud Platforms with an understanding of Google Cloud Platform (GCP). - **Infrastructure as Code:** Proficiency in Terraform for infrastructure automation. - **Network and Security:** Proficient in understanding of network and security principles. - **DevSecOps:** Advanced skills in DevSecOps practices, with a focus on shift-left thinking and zero-touch automation. - **Architecture Patterns:** Strong experience working with common architecture patterns and an understanding of AI/ML workflows. - **Programming:** Basic knowledge of programming languages like Python. - **BDD:** Strong experience with Behavior Driven Development (BDD) creation for testing. **Soft Skills:** - **Teamwork:** Ability to work effectively in a collaborative team environment. - **Communication:** Strong verbal and written communication skills. - **Problem-Solving:** Excellent problem-solving and analytical skills. - **Adaptability:** Ability to adapt to changing technologies and environments.