GCP/GKE DevOps Lead

Title: GCP/GKE DevOps Lead

Location: Jersey City, New Jersey

Minimum Experience: 08 Years

Kubernetes and Compute Platform

• Design, operate, and upgrade GKE clusters in both Autopilot and Standard modes, including custom compute classes, node pool configuration, and capacity management.
• Manage multi-cluster architecture using GKE Fleet, Multi-Cluster Ingress, and Multi-Cluster Gateway.
• Implement workload autoscaling using KEDA and the Custom Metrics Adapter for event-driven and metrics-based scaling.
• Manage cluster add-ons and operational tooling, including the Secrets Store CSI Driver, Reloader, ConfigMaps, and ingress configuration.
• Deploy and operate serverless workloads on Cloud Run and Cloud Functions, and provision Compute Engine instances where required.

Infrastructure as Code

• Own and maintain a modular Terraform codebase managed through Terraform Cloud, with environment-specific configurations across development, QA, staging, and production.
• Build and maintain reusable Terraform modules and enforce consistent standards, reviews, and plan/apply workflows.
• Manage Harness configuration as code through Terraform, including service, environment, and pipeline onboarding.

Networking, Edge, and Certificate Management

• Manage global and static IP addressing, load balancing, and ingress for internet-facing and internal services.
• Configure and maintain edge security using Google Cloud Armor and Imperva WAF.
• Manage SSL/TLS certificates and automated certificate expiry monitoring to prevent service disruption.

Security and Identity

• Define and enforce least-privilege IAM policies, service accounts, and Workload Identity through Terraform.
• Enforce supply-chain security using Binary Authorization on production clusters.
• Manage secrets through Google Secret Manager and the Secrets Store CSI Driver, and manage encryption keys in Cloud KMS, including key rotation alerting.
• Support runtime application security tooling (e.g., Oligo) and contribute to DevSecOps practices across the delivery lifecycle.

Data and Messaging Services

• Provision and manage Cloud SQL (PostgreSQL) instances, including database grants, certificates, backups, and performance.
• Manage Memorystore, Firestore, and Cloud Storage resources, including access controls and lifecycle policies.
• Support event-driven architectures built on Pub/Sub.

CI/CD and Source Control

• Build, maintain, and optimise Harness CI/CD pipelines for GKE, Cloud Run, and Cloud Functions deployments, including progressive delivery and automated rollback.
• Manage GitHub repositories, branching strategies, pull request workflows, and automated code review integrations.
• Create and optimise Docker images for security, size, and build performance, and manage images in Artifact Registry.
• Track and deliver work through Jira using agile practices.

Observability, Reliability, and Cost

• Configure and maintain monitoring and alerting through Splunk detectors and Google Cloud Monitoring, integrated with Microsoft Teams notifications.
• Define SLOs/SLIs, lead incident response, and conduct blameless post-incident reviews.
• Drive cost optimisation through workload scheduling, scale-to-zero environments, rightsizing, and resource governance.

Automation and AI-Enabled Engineering

• Develop automation and tooling using Python, Bash.
• Use AI-assisted development tools (Gemini, Claude, GitHub Copilot) to accelerate Terraform authoring, pipeline development, troubleshooting, and documentation.
• Identify, propose, and prototype AI agents that automate DevOps workflows, such as Terraform plan review, pipeline failure analysis, incident triage, certificate and key-expiry management, IAM access requests, and cost reporting.
• Promote responsible use of AI tools, ensuring outputs are reviewed and that sensitive data and credentials are protected.