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Job Summary: Design, build, and operate secure, scalable, and cost-effective Cloud infrastructure on GCP to support AI workloads. Key Highlights: 1. Design, construction, and operation of Cloud infrastructure on GCP. 2. Specialized support and optimization of AI workloads. 3. Infrastructure-as-Code (IaC) automation using Terraform. **Job Mission** You will be responsible for designing, building, and operating secure, scalable, and cost\-effective Cloud infrastructure on GCP (Google Cloud Platform), serving as the company's technological foundation. This role is primarily accountable for computing, networking, and storage services. Additionally, you will provide specialized support and the necessary infrastructure to enable and optimize Artificial Intelligence workloads, ensuring data science teams can deploy and operate their models on a robust and well-managed platform. **What responsibilities and tasks will you handle?** * Core GCP Infrastructure Management (Compute and Networking): Administer, secure, and optimize Compute Engine resources, Google Kubernetes Engine (GKE), VPC networks, firewalls, and IAM policies. * Infrastructure-as-Code (IaC) Automation: Use Terraform as the primary tool for versioned deployment and management of all cloud infrastructure, ensuring consistency and repeatability. * Storage and Database Administration: Manage storage solutions such as Cloud Storage and relational databases (Cloud SQL), ensuring performance, backup, and security. * AI Platform Enablement: Deploy and manage infrastructure required for AI solutions, including configuration of environments in Vertex AI and management of datasets in BigQuery. * AI Workload Support: Collaborate with data teams to resolve performance, connectivity, and permission issues related to model training and inference on the GCP platform. **Requirements** * University degree or bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or related fields. * Experience: At least 5 years of experience managing cloud systems on GCP, including at least 1\-2 years of hands-on experience supporting AI platforms and workloads (Vertex AI, BigQuery). * Certification combination is highly desirable. Primary: Google Professional Cloud Architect or Professional Cloud DevOps Engineer. Complementary: Google Professional Machine Learning Engineer. **What competencies would we like you to have?** * Ability to effectively identify, analyze, and resolve complex technical problems. * Skill in evaluating information, analyzing complex situations, and making well-founded decisions. * Attention to detail to ensure accuracy in system configuration and administration. * Aptitude to collaborate and work effectively within multidisciplinary teams. * Ability to clearly and concisely communicate technical information to diverse audiences. * Capacity to efficiently organize and prioritize tasks in a dynamic environment. **What do we offer?** * Permanent contract. * Compensation composed of fixed and variable components. * Office hours with flexibility in start and end times. * Hybrid work mode. * Flexible Compensation Plan with Cobee.
