Job Title : Architect (Level: Manager)
Address : Minneapolis, Minnesota
Job Duration : 3-6 Months
Experience : 13 years
Job Title: Google Cloud Platform Cloud Architect (Forward Deployed Engineering)
About the Role
We are looking for a hands-on Google Cloud Platform Cloud Architect / Forward Deployed Engineer to design, build, and operationalize enterprise-grade Google Cloud platforms.
The role covers end-to-end ownership from Day 0 Google Cloud Platform setup through production deployment, Infrastructure as Code (IaC), SRE, observability, and Agentic AI platform enablement.
Key Responsibilities
Design and implement enterprise Google Cloud Platform landing zones, IAM, VPC, Shared VPC, firewalls, Private Service Connect, and security controls.
Build and manage infrastructure using Terraform (Terragrunt preferred) with 100% Infrastructure as Code.
Establish SRE practices including SLIs, SLOs, SLAs, error budgets, incident management, disaster recovery, and automation.
Implement monitoring and observability using Google Cloud Operations Suite, Cloud Monitoring, Cloud Logging, Prometheus, Grafana, OpenTelemetry, or Datadog.
Design Multi-Zone/Multi-Region, Active-Active/Active-Passive architectures with backup, failover, business continuity, and RTO/RPO planning.
Implement secure authentication and authorization using OAuth 2.0, OIDC, SAML, Zero Trust, IAM, API security, Secrets Manager, and KMS.
Deploy AI infrastructure using Vertex AI, GKE, Cloud Run, vector databases, and orchestration frameworks.
Build CI/CD pipelines using GitHub Actions, Cloud Build, or GitLab CI.
Collaborate with engineering, product, and client teams to deliver scalable cloud solutions.
Required Qualifications
6 8 years of hands-on experience designing and operating enterprise workloads on Google Cloud Platform.
Google Cloud Platform Professional Cloud Architect certification preferred.Experience delivering at least 3 enterprise-scale Google Cloud Platform production projects.
Strong expertise in Terraform, Google Cloud Platform networking, IAM, security, and Infrastructure as Code.
Hands-on experience with SRE, observability, distributed tracing, monitoring, logging, and alerting.
Experience supporting AI/LLM infrastructure, including Vertex AI, GKE, Cloud Run, and model hosting.
Strong scripting skills in Python, Bash, along with Docker and modern CI/CD tools.
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