Cyber Operate Manager - GCP Cloud DevOps Engineer
About The Position
Deloitte is seeking a Lead Managed Services Engineer II for its Cyber Operate team to design, automate, and operate enterprise-scale cloud capabilities that support clients’ critical cyber assets. The role applies Google Cloud Platform (GCP), Terraform, infrastructure as code, and DevOps practices to build secure, scalable, and reliable solutions. The engineer collaborates with Cyber Operate, data engineering, and artificial intelligence and machine learning (AI/ML) teams to meet evolving client needs, support operational excellence, and deliver cloud solutions securely. The position includes designing and maintaining Terraform modules and infrastructure-as-code workflows; provisioning and operating GCP services; developing CI/CD pipelines and governance practices; and implementing monitoring, observability, high availability, and disaster recovery. The engineer investigates production incidents, documents root causes, creates operational runbooks and architecture documentation, and supports infrastructure for data platforms and AI workloads, including Vertex AI Agent Engine, Vertex AI Search, and Model Armor. The role requires residence within commuting distance of the assigned office, with an average of one day per week co-located, though this may vary by project and client location. Travel averages 20–25%. Recruiting for this role ends on 12/31/2026.
Requirements
- At least 6 years of experience with Terraform module development and GCP infrastructure provisioning across development, test, staging, and production environments.
- At least 6 years of experience configuring Cloud Run, BigQuery, Cloud Storage, Firestore, Secret Manager, Google Cloud Load Balancing, GKE, IAM, VPCs, subnets, firewall rules, private connectivity, DNS, and SSL certificates.
- At least 6 years of experience developing CI/CD pipelines with Cloud Build or GitHub Actions for infrastructure and application deployments, including version control, code review, and deployment processes.
- At least 6 years of experience using Cloud Monitoring for monitoring, alerting, logging, and observability; investigating production incidents; developing operational runbooks; and documenting architecture.
- At least 6 years of experience building APIs or data connectors using Python, Cloud Functions, or Cloud Run, and supporting data platforms using BigQuery, Dataflow, Pub/Sub, Cloud Storage, or Cloud Composer.
- At least 6 years of experience supporting infrastructure for Vertex AI Agent Engine, Vertex AI Search, or Model Armor.
- At least 6 years of experience configuring IAM policies, service accounts, and security controls for cloud infrastructure.
- Must reside within commuting distance of the assigned office and be able to commute daily if required, without overnight accommodations.
- Ability to travel an average of 20–25%, depending on work and clients.
- Ability to work independently and collaboratively, communicate effectively, maintain attention to detail and quality, build professional relationships, lead workstreams, prioritize multiple tasks in a dynamic environment, meet deadlines, and mentor others.
Nice To Haves
- Master’s degree.
- Google Cloud Professional Cloud DevOps Engineer certification.
- HashiCorp Certified: Terraform Associate certification.
- Experience supporting identity lifecycle management, security operations, threat intelligence, or application security.
Responsibilities
- Design, build, and maintain Terraform modules and infrastructure-as-code workflows across development, test, staging, and production environments.
- Provision and operate GCP services, including Cloud Run, BigQuery, Cloud Storage, Firestore, IAM, Secret Manager, Google Cloud Load Balancing, GKE, VPCs, subnets, firewall rules, private connectivity, DNS, and SSL certificates.
- Develop CI/CD pipelines, infrastructure versioning, automated code-review processes, governance controls, and deployment strategies for infrastructure and applications.
- Implement monitoring, alerting, logging, observability, high availability, and disaster recovery practices.
- Investigate production incidents and document root-cause findings.
- Create operational runbooks, architecture documentation, and support procedures for managed cloud environments.
- Partner with data engineering and AI/ML teams to support infrastructure for data platforms and AI workloads, including Vertex AI Agent Engine, Vertex AI Search, and Model Armor.
- Lead projects or workstreams, manage and prioritize multiple tasks, and mentor others with clear guidance.
Benefits
- May be eligible to participate in a discretionary annual incentive program, subject to program rules and relevant factors including individual and organizational performance.
- Opportunities for professional development through on-the-job learning, formal development programs, leadership opportunities, mentorship, and skill building.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
