Role: IT Infrastructure Services - Other
Industry Type: IT Services & Consulting
Department: IT & Information Security
Employment Type: Full Time, Permanent
Role Category: IT Infrastructure Services
UG: Any Graduate
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.