Job Description

Job Summary

Position Overview

The Google Cloud AI DevOps Engineer (8+ years) is responsible for designing, building, and managing end‑to‑end pipelines and infrastructure on Google Cloud Platform (GCP). This role combines deep cloud engineering expertise with DevOps best practices to enable scalable CI/CD, automated deployments, and robust monitoring for AI/ML and data-driven platforms. The engineer collaborates closely with data scientists, platform engineering, and infrastructure teams to deliver secure, reliable, and efficient GCP-based solutions.

Key Responsibilities

Design, implement, and maintain automated build and deployment pipelines using GCP services such as Cloud Build, Cloud Functions, GKE, and GCE.

• Develop and manage infrastructure using IaC tools (Terraform, Cloud Deploy, Cloud Build, Jenkins, Packer, Terragrunt) to ensure consistent and scalable deployments.
• Create and optimize container images and manage container registries.
• Integrate and manage DevOps tools such as Jenkins, GitHub Actions, Bitbucket Pipelines, ArgoCD, and Tekton.
• Implement monitoring and logging using Cloud Operations, Prometheus, and Grafana.
• Apply automation and security best practices ensuring reproducibility, scalability, and compliance.
• Manage source control repositories (GitHub, Bitbucket) including branching, code reviews, and releases.
• Provide technical guidance, documentation, and best-practice enablement.

Skill Requirements

• Experience building pipelines and infrastructure on GCP using tools such as Vertex AI, GKE, Cloud Build, and Cloud Functions.
• Expertise in DevOps methodologies and CI/CD tools (Jenkins, GitHub Actions, Bitbucket Pipelines, ArgoCD, Tekton).
• Deep knowledge of Docker, Dockerfiles, and container registries.
• Hands-on experience with Terraform, Deployment Manager, and scripting (Python, Bash).
• Strong Git-based workflow experience.
• Monitoring/logging experience using Cloud Operations, Prometheus, Grafana.
• Strong collaboration skills with data science and platform engineering teams.
• Understanding of cloud security, IAM, and governance.
• Experience tuning and scaling AI workloads on GCP.
• Preferred: Google Cloud DevOps or AI Engineer certifications.

Other Requirements

Qualifications & Certifications

• Bachelor’s degree in IT, Engineering, or a related field; MBA/management qualification is a plus.
• GCP Professional DevOps Engineer certification (required).
• GCP Professional Cloud Architect certification (preferred).
• Terraform Associate certification.