Security Engineer

Requirement Notes (Candidate Job description below) : We are looking for a Senior (5+ years) GCP Security Engineer who lives on GCP and can own the security architecture end-to-end, not just advise on it. You will design guardrails, write Terraform, integrate with Harness CI/CD pipelines, and partner with engineering teams to ensure every resource deployed is secure by default. This role is GCP-first. Familiarity with AWS and Azure is a plus, but your day-to-day will be deep in Google Cloud: securing GKE workloads, governing AI pipelines on Vertex AI, managing identities via ICAM, and using native GCP security services to detect and respond to threats.

**** THE MANAGER WOULD LIKE TO SEE CERTIFICATIONS.

Must Have:

• Experience with GCP security services including IAM, VPC Service Controls, Cloud Armor, KMS, Secret Manager, DLP, and SCC.
• Strong Elastic SIEM experience including log ingestion, detection engineering, alert management, and threat correlation.
• Production-level Terraform experience including module development, infrastructure automation, and state management.
• Strong knowledge of Kubernetes and GKE security including pod security admission, network policies, Workload Identity, and Binary Authorization.

MANAGERS NOTES:

• Looking for a Security-focused GCP Engineer
• Risk/Compliance
• Not DevOps or Logging
• Must be fully hands-on developing
• Should not rely on AI to assist with development

Job Description:

CANDIDATES MUST COMMIT TO A FINAL IN PERSON, ONSITE INTERVIEW (TRAVEL PAID BY THE CLIENT).

We are looking for a Senior GCP Security Engineer who lives on GCP and can own the security architecture end-to-end, not just advise on it. You will design guardrails, write Terraform, integrate with Harness CI/CD pipelines, and partner with engineering teams to ensure every resource deployed is secure by default. This role is GCP-first. Familiarity with AWS and Azure is a plus, but your day-to-day will be deep in Google Cloud: securing GKE workloads, governing AI pipelines on Vertex AI, managing identities via ICAM, and using native GCP security services to detect and respond to threats.

What You'll Bring:

• 5+ years of experience in cloud security, with the majority focused on GCP environments.
• Deep hands-on experience with GCP security services including IAM, VPC Service Controls, Cloud Armor, KMS, Secret Manager, DLP, and SCC.
• Strong Elastic SIEM experience including log ingestion, detection engineering, alert management, and threat correlation.
• Production-level Terraform experience including module development, infrastructure automation, and state management.
• Experience integrating security controls into CI/CD pipelines using Harness or equivalent platforms.
• Strong knowledge of Kubernetes and GKE security including pod security admission, network policies, Workload Identity, and Binary Authorization.
• Hands-on experience with ICAM or enterprise identity platforms governing non-human identities and workload access.
• Practical knowledge of AI/ML security including Vertex AI workload protection, LLM API governance, and training data security.

Preferred Qualifications

• Google Professional Cloud Security Engineer or Professional Cloud Architect certification.
• Experience with policy-as-code tooling such as OPA/Rego, Sentinel, or Checkov.
• Familiarity with AWS security services including IAM, GuardDuty, SCPs, and multi-cloud security architectures.
• Experience with Cribl Stream or similar log routing technologies integrated with Elasticsearch.
• Understanding of compliance-driven security requirements including NY DFS 23 NYCRR 500, NAIC, NIST CSF, CIS Benchmarks, and ISO 27001.
• Working knowledge of enterprise identity platforms including SailPoint, CyberArk, Ping Identity, Active Directory, and LDAP.
• Experience securing AI agent frameworks such as LangChain or Vertex AI Agent Builder.

Primary Technology Stack:

• Infrastructure as Code: Terraform (required), Harness CI/CD, ICAM
• Identity: GCP Workload Identity Federation, service account governance, ICAM, SailPoint, CyberArk, Ping Identity, Active Directory, LDAP
• AI/ML: Vertex AI Agent Builder, Gemini APIs, BigQuery ML, RAG pipelines
• Secondary: AWS (IAM, GuardDuty, Bedrock), Azure (familiarity acceptable)