Job Summary
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
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.