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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.
Skill Requirements
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.
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.
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