GCP DevOps Engineer

Overview

We are seeking a highly skilled GCP DevOps Engineer with Machine Learning expertise to design, implement, and manage scalable, secure, and cost-effective cloud infrastructure on Google Cloud Platform (GCP). This role involves building robust CI/CD pipelines, automating infrastructure provisioning, and supporting ML workflows using Vertex AI. The ideal candidate will have strong experience in cloud architecture, container orchestration, Infrastructure as Code (IaC), and ML lifecycle automation.

Responsibilities

• Cloud Infrastructure Management: Design and manage scalable, secure, and cost-optimized infrastructure on GCP.
• CI/CD Automation: Build and maintain pipelines using Cloud Build, Cloud Deploy, and integrate with Artifact Registry.
• Containerized Application Deployment: Deploy and manage workloads using Cloud Run, Google Kubernetes Engine (GKE), and App Engine.
• Infrastructure Automation: Implement IaC and workflows using Terraform, Python, and Cloud Functions.
• ML Workflow Integration: Support Vertex AI for end-to-end ML lifecycle automation (training, deployment, monitoring).
• Monitoring & Logging: Implement observability using Cloud Monitoring, Cloud Logging, Prometheus, and Grafana.
• Network Design: Configure secure and scalable VPC networks, firewall rules, subnets, VPC peering, Private Service Connect, and load balancers.
• Security & Compliance: Apply IAM best practices, enforce security policies using Security Command Center, Policy Intelligence, and Organization Policies.
• IaC & GitOps: Develop and maintain Terraform modules, GitOps workflows, and manage repositories in Cloud Source Repositories.
• Container Orchestration: Manage workloads using Docker, Kubernetes, and Helm charts.
• Incident Management: Monitor performance, conduct RCA, and implement incident response procedures.
• Cost Optimization: Analyze billing, implement rightsizing, and apply scheduling policies for cost efficiency.
• Documentation: Maintain architecture diagrams, runbooks, and operational knowledge base.
• Cross-functional Collaboration: Work with ML and data science teams to ensure reliable infrastructure for experimentation and production workloads.
• Business Continuity: Ensure high availability, disaster recovery, and continuity planning.
  
  
  

• Strong experience with Google Cloud Platform (GCP) services (Compute Engine, GKE, Cloud Run, App Engine, VPC, IAM).
• Proficiency in CI/CD tools: Cloud Build, Cloud Deploy, Artifact Registry.
• Expertise in Infrastructure as Code (IaC) using Terraform and GitOps workflows.
• Hands-on experience with containerization (Docker, Kubernetes, Helm).
• Programming skills in Python for automation and scripting.
• Familiarity with Vertex AI and ML lifecycle management.
• Knowledge of monitoring and observability tools: Cloud Monitoring, Prometheus, Grafana.
• Strong understanding of networking concepts: VPC design, firewall rules, load balancing.
• Security best practices for cloud environments and CI/CD pipelines.
  
  
  

• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced, agile environment.