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The Google Cloud AI DevOps Engineer 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.
- 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.
Required Skills & Expertise
- 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.
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.
