2 of 2 Google Compute Engine Jobs

systems. This is a hands-on technical role with strategic impact across infrastructure, automation, and security. Key Responsibilities Infrastructure & Cloud Engineering Design, build, and manage scalable, resilient infrastructure on Google Cloud Platform (GCP) . Implement Infrastructure as Code (IaC) using Terraform to ensure consistent and secure deployments. Utilize GCP services such as Compute Engine , Cloud Run , Cloud … Functions , BigQuery , and Kubernetes to support AI workloads. CI/CD & Automation Develop and maintain CI/CD pipelines using Google Cloud Build , Jenkins , and GitHub Actions . Automate deployment workflows and operational tasks to improve efficiency and reduce manual errors. Drive adoption of DevOps best practices across engineering teams. Containerization & Orchestration Build and manage containerized applications using Docker … and alerting systems using Cloud Monitoring , Cloud Logging , Prometheus Troubleshoot infrastructure issues and ensure minimal downtime for critical AI services. Required Skills Strong hands-on experience with GCP services : Compute Engine, Kubernetes, Cloud Storage, BigQuery, Cloud Run. Proficient in scripting with Python or Bash . Deep understanding of Docker and Kubernetes for containerization and orchestration. Expertise in CI More ❯

understand customer challenges, design and present compelling solutions, and guide customers through the implementation and adoption of our products and services, with a focus on Generative AI solutions on Google Cloud. This role requires a blend of technical depth, business acumen, and strong communication skills, with a specialization in applying Generative AI technologies to solve complex business problems. A … blend of strong technical skills in cloud-native technologies, including AI/ML, and excellent communication and problem-solving abilities to assist customers with their cloud solutions. Core Focus: Google Cloud Platform (GCP) Expertise Cloud-Native Proficiency: Kubernetes, containers, and serverless architectures. GCP Service Mastery: Deep knowledge of core GCP services (Compute Engine, Storage, SQL, BigQuery, etc. … AI, including AutoML, custom training, and pre-trained models. Understanding of Vertex AI's role in enabling generative AI solutions. GCP AI/ML Services: Knowledge of other relevant Google Cloud AI/ML services and APIs (e.g., Natural Language API, Vision API). Infrastructure Automation: IaC with Terraform or Cloud Deployment Manager. Cloud Solution Design: Building scalable, secure More ❯