GCP Platform Engineer: SRE, Terraform & Kubernetes

Crown Solutions Inc; Memphis (TN); On-site; USD 110,000 - 150,000; Full time

Job summary

Crown Solutions Inc. in Memphis, TN is seeking a Platform Engineer to design, build, and secure scalable infrastructure on Google Cloud Platform. You will collaborate with Kubernetes, infrastructure-as-code, security, and data tooling to keep systems reliable, observable, and easy for product teams to build on.

You’ll combine SRE practices with platform engineering—focusing on reliability, incident response, and automation with Terraform, IAM hardening, and cost governance across GCP workloads.

Responsibilities

• Design, build, and maintain infrastructure on Google Cloud Platform using Terraform.
• Operate and improve GKE clusters: scheduling, autoscaling, networking, and container security hardening.
• Apply SRE principles to production systems: define and track SLOs/SLIs, build dashboards and alerting, participate in on-call rotation, and contribute to incident response.
• Implement and maintain IAM policies and security controls aligned with least-privilege and compliance requirements.
• Support and extend data platform infrastructure (BigQuery, Dataflow) and related access controls.
• Improve observability across the platform with Cloud Monitoring, Cloud Logging, Prometheus, and Grafana.
• Collaborate with software teams to provide self-service infrastructure patterns and reusable Terraform modules.
• Participate in capacity planning, cost optimization, and disaster recovery planning for GCP workloads.

Job description

Crown Solutions Inc. in Memphis, TN is seeking a Platform Engineer to design, build, and secure scalable infrastructure on Google Cloud Platform. You will collaborate with Kubernetes, infrastructure-as-code, security, and data tooling to keep systems reliable, observable, and easy for product teams to build on.

You’ll combine SRE practices with platform engineering—focusing on reliability, incident response, and automation with Terraform, IAM hardening, and cost governance across GCP workloads.