> Markdown version of [/jobs/ext/3550546-gcp-security-engineer](https://www.wearedevelopers.com/jobs/ext/3550546-gcp-security-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GCP Security Engineer - **Company:** The Real Estate - **Location:** Elmsford, NY, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Cloud Computing, Cloud Computing Security, Continuous Integration, Elasticsearch, Identity and Access Management, Security Information and Event Management, Software Deployment, Google Cloud, Amazon Virtual Private Cloud (VPC), Kubernetes, Infrastructure Automation Frameworks, Terraform - **Published:** September 30, 2026 - **Apply:** https://www.thejobnetwork.com/job/55d8df02-6e01-483b-ac17-c0ad8ad66349/senior-gcp-security-engineer ## About the Role * 5+ years of cloud security experience with significant recent GCP depth. \n * Strong hands-on experience implementing security controls within Google Cloud. \n * Production-level Terraform experience, including reusable modules and infrastructure automation. \n * Strong Kubernetes and GKE security experience. \n * Deep knowledge of GCP IAM, service accounts, Workload Identity, and workload access. \n * Experience with multiple GCP security technologies such as SCC, VPC Service Controls, Cloud Armor, KMS, Secret Manager, and DLP. \n * Experience incorporating security controls into modern CI/CD environments. \n * Practical understanding of AI / ML security, ideally involving Vertex AI or comparable enterprise GenAI platforms. \n * Ability to work directly with engineering teams and remain personally hands-on. ## Description This is a hands-on engineering position for someone who can move between architecture and implementation. You will design cloud security guardrails, automate controls through Terraform and CI/CD, secure Kubernetes workloads and cloud identities, and work closely with engineering teams deploying applications and AI workloads across GCP.