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# Cloud Engineer (GCP)

- **Company:** Accenture
- **Location:** Fairfax, VA, United States
- **Experience:** Expert
- **Salary:** $81,000.0 - $154,700.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Cloud Engineering, Continuous Integration, Custom Software, Data Security, DevOps, Digital Architecture, Github, Identity and Access Management, Network Segmentation, Cloud Services, Zero Trust Network Access, Runbook, Data Logging, Google Cloud, Cloud Platform System, System Availability, Multi-Cloud, Build Server, Amazon Virtual Private Cloud (VPC), Containerization, Deployment Automation, Terraform, Docker
- **Published:** October 25, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=843c7ab018166335

## About the Role

* Minimum 5+ years of hands-on cloud engineering experience.
 * Strong delivery experience on GCP, plus working knowledge of AWS GovCloud.
 * Expertise deploying Docker-based custom software at scale.
 * Strong Terraform engineering capability.
 * Have a CI/CD-first mindset; comfortable designing DevOps patterns end-to-end.
 * Comfort working in secure, regulated, and cross-domain environments.
 * Active Top Secret clearance required with CI poly.
 * Must be willing to work onsite in Washington, DC.

## Description

We are looking for an experienced Cloud Engineer with deep hands on expertise in multi cloud environments and a strong emphasis on Google Cloud Platform. This role is highly technical and requires an engineer who can both implement cloud infrastructure and think at an architect level - designing scalable patterns, building automated deployment frameworks, and supporting enterprise AI workloads across multiple security domains and compliance boundaries. You will work heavily with custom software deployments, Docker-based workloads, Cloud Run, and eventually GKE, while ensuring infrastructure is automated, secure, compliant, and built via Terraform and CI/CD pipelines rather than console-driven operations. You're already a strong cloud practitioner who is naturally curious, self-driven, and comfortable exploring new services independently - including using AI tools to accelerate learning and design. This role supports deployments across Unclassified and Classified fabrics, requiring
strict adherence to FedRAMP, Zero Trust, and cross-domain (CDS) requirements., Multi Cloud Infrastructure (GCP Focused) Provision and configure cloud resources with a strong emphasis on GCP (Cloud Run, Vertex AI, Artifact Registry, Secret Manager, IAM). Design scalable patterns for containerized workloads, beginning with Cloud Run and expanding to GKE as needed. Deploy and manage Docker-based applications across GCP and AWS GovCloud. Support AI workload hosting using Vertex AI (GCP) and Bedrock (AWS) in secure, multi-domain environments. Infrastructure as Code & DevOps Automation Build all infrastructure using Terraform (preferably modular patterns) and maintain automation-first standards. Write scripts to support deployment, automation, and operational workflows. Maintain CI/CD pipelines (GitHub Actions, Cloud Build, etc.) for reproducible deployments across all security fabrics. Implement GitOps and DevOps best practices; avoid console based configuration. Secure, Classified, and Cross-Domain Cloud Operations Build and maintain cloud architectures spanning
Unclassified and Classified environments with strict security boundaries. Implement and troubleshoot cross-domain solutions (CDS), secure data transfer patterns, and enclave-specific configurations. Ensure Zero Trust-aligned configurations for each security domain. Support FedRAMP compliance and ATO-related activities for multi-domain deployments. Enterprise-Scale Architecture & Operational Excellence Design enterprise-grade cloud patterns that scale beyond prototypes - multi-tenant environments, reusable modules, structured network segmentation, and standardized deployment frameworks. Configure VPC networking, IAM policies, access controls, and segmentation strategies across multiple clouds and domains. Implement monitoring, logging, and alerting to ensure platform reliability, security, and performance. Support cloud migration activities transitioning on-prem systems into multi-cloud architectures hosting AI workloads. Collaboration & Continuous Learning Collaborate closely with Cloud
Solution Architects, DevOps Engineers, Data Engineers, and AI Developers. Explore and learn new cloud services proactively; identify which services best support architectural and business goals. Leverage AI tools to accelerate learning, analysis, troubleshooting, and ideation. Document architecture, configurations, runbooks, operational procedures, and cross-domain designs.