Senior GCP Cloud Developer / Cloud Architect – AI & Generative AI
Key Responsibilities
- Define and continuously evolve GCP architecture standards and patterns within the AI domain.
- Design and establish governance models at scale for AI capabilities, particularly Vertex AI and Gemini.
- Define and promote best practices for security, governance, automation, and scalability of AI capabilities.
- Act as a technical reference for strategic AI-related decisions within the GCP ecosystem.
- Contribute to the conceptualization, development, and deployment of AI solutions for employees.
- Support the evolution of the organization's GCP Cloud Center of Excellence (CCoE).
- Define reusable architecture patterns and technical guidelines for AI workloads.
- Collaborate with multidisciplinary teams to ensure alignment between business requirements, architecture, security, and cloud engineering.
- Promote automation and Infrastructure as Code practices across cloud and AI environments.
Must-Have Requirements
- 5+ years of experience in Cloud Engineering, Cloud Architecture, or related technical roles.
- Strong technical expertise in Google Cloud Platform (GCP).
- Specific knowledge of Vertex AI and Generative AI capabilities.
- Proven ability to define architecture standards, patterns, and best practices.
- Strong knowledge of Infrastructure as Code (IaC), particularly Terraform.
- Understanding of cloud security, governance, automation, and scalability.
- Ability to work effectively in multidisciplinary teams.
- Strong architectural thinking and the ability to act as a technical advisor on strategic initiatives.
Valuable / Nice-to-Have Skills
- Functional and technical understanding of Gemini Enterprise.
- Experience integrating AI capabilities with Google Workspace.
- Experience designing landing zones in complex, heterogeneous, and enterprise-scale environments.
- Previous experience contributing to Cloud Centers of Excellence (CCoE).
- Experience with enterprise AI governance and responsible deployment of Generative AI solutions.
- Experience designing scalable architectures for AI agents, connectors, and cloud-based AI ecosystems.
Senior GCP Cloud Developer / Cloud Architect – AI & Generative AI
Key Responsibilities
- Define and continuously evolve GCP architecture standards and patterns within the AI domain.
- Design and establish governance models at scale for AI capabilities, particularly Vertex AI and Gemini.
- Define and promote best practices for security, governance, automation, and scalability of AI capabilities.
- Act as a technical reference for strategic AI-related decisions within the GCP ecosystem.
- Contribute to the conceptualization, development, and deployment of AI solutions for employees.
- Support the evolution of the organization's GCP Cloud Center of Excellence (CCoE).
- Define reusable architecture patterns and technical guidelines for AI workloads.
- Collaborate with multidisciplinary teams to ensure alignment between business requirements, architecture, security, and cloud engineering.
- Promote automation and Infrastructure as Code practices across cloud and AI environments.
Must-Have Requirements
- 5+ years of experience in Cloud Engineering, Cloud Architecture, or related technical roles.
- Strong technical expertise in Google Cloud Platform (GCP).
- Specific knowledge of Vertex AI and Generative AI capabilities.
- Proven ability to define architecture standards, patterns, and best practices.
- Strong knowledge of Infrastructure as Code (IaC), particularly Terraform.
- Understanding of cloud security, governance, automation, and scalability.
- Ability to work effectively in multidisciplinary teams.
- Strong architectural thinking and the ability to act as a technical advisor on strategic initiatives.
Valuable / Nice-to-Have Skills
- Functional and technical understanding of Gemini Enterprise.
- Experience integrating AI capabilities with Google Workspace.
- Experience designing landing zones in complex, heterogeneous, and enterprise-scale environments.
- Previous experience contributing to Cloud Centers of Excellence (CCoE).
- Experience with enterprise AI governance and responsible deployment of Generative AI solutions.
- Experience designing scalable architectures for AI agents, connectors, and cloud-based AI ecosystems.
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