Principal Cloud Engineer

GXO Logistics•Greenwich, CT

About The Position

As the Principal Cloud Engineer, Google Cloud, you will serve as one of GXO's senior technical leaders responsible for building, implementing, and scaling our Google Cloud Platform. This is a deeply hands-on engineering role focused on delivering secure, production-ready cloud infrastructure, platform automation, Kubernetes, networking, and enterprise AI platform capabilities. Working alongside architects, security teams, and engineering partners, you'll transform cloud strategy into scalable, resilient, and operational solutions that power GXO's next generation of enterprise platforms. If you're looking for an opportunity to build the cloud foundation for enterprise AI while shaping the future of Google Cloud engineering at global scale, join us at GXO.

Requirements

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent work experience.
Google Cloud Professional Cloud Architect certification.
10–15+ years of experience in cloud engineering, platform engineering, infrastructure engineering, or distributed systems.
5–7+ years of hands-on experience designing, building, and operating enterprise-scale Google Cloud environments.
Demonstrated experience building and scaling enterprise cloud platforms rather than solely operating existing environments.
Deep expertise in Google Cloud resource hierarchy, organization policies, IAM, Workload Identity Federation, networking, Shared VPC, Cloud KMS/CMEK, Identity-Aware Proxy (IAP), logging, monitoring, and secure cloud operations.
Extensive hands-on experience with Google Kubernetes Engine (GKE), Kubernetes networking, autoscaling, Cloud Run, ingress/egress, and production operations.
Strong experience implementing Infrastructure as Code using Terraform, GitOps, CI/CD pipelines, Artifact Registry, and policy-as-code.
Proven expertise implementing zero-trust cloud security including least privilege access, Binary Authorization, encryption, secrets management, audit logging, and secure operational controls.
Experience implementing enterprise observability, reliability engineering, and FinOps practices for cloud platforms.
Experience building reusable platform engineering capabilities and self-service cloud infrastructure.
Experience supporting enterprise AI, analytics, machine learning, or large language model (LLM) platforms on Google Cloud.
Strong written and verbal communication skills with experience documenting engineering standards, technical designs, and operational runbooks.
Demonstrated ability to mentor engineers while collaborating effectively with architects, security teams, infrastructure teams, and technology partners.
Ability to operate effectively with minimal supervision in a fast-paced, global enterprise environment.

Nice To Haves

Google Cloud Professional Security Engineer certification.
Google Cloud Professional DevOps Engineer certification.
Google Cloud Professional Machine Learning Engineer certification.
Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD).
HashiCorp Terraform Associate certification.
Experience supporting AI platforms utilizing Vertex AI, Gemini Enterprise Agent Platform, LiteLLM, MCP, AI gateways, agent runtimes, or comparable technologies.
Experience integrating Google Cloud workloads with Snowflake using OAuth, RBAC, masking policies, row-level security, and governed data access.
Experience implementing enterprise FinOps practices for large-scale cloud environments.
Experience building secure multi-tenant cloud platforms and reusable engineering frameworks.
Demonstrated success collaborating across enterprise architecture, cloud engineering, security, and infrastructure organizations while contributing to shared engineering standards and best practices.

Responsibilities

Build and scale GXO's Google Cloud Platform foundation, including organization hierarchy, landing zones, Shared VPC, IAM, Workload Identity Federation, Secret Manager, Cloud KMS/CMEK, Identity-Aware Proxy (IAP), and Cloud Logging and Monitoring.
Develop reusable Terraform modules, project factory patterns, secure-by-default configurations, and standardized deployment patterns across multiple environments.
Engineer and operate production-grade Google Kubernetes Engine (GKE) platforms, including cluster architecture, networking, ingress/egress, autoscaling, observability, and operational runbooks.
Translate enterprise architecture into secure, scalable, production-ready cloud implementations.
Build Infrastructure as Code (IaC) standards through reusable Terraform modules, GitOps workflows, CI/CD pipelines, policy guardrails, and platform automation.
Develop and maintain CI/CD pipelines using Cloud Build, GitHub Actions, Artifact Registry, and related cloud-native tooling.
Automate cloud platform operations, integrate Google Cloud APIs, and reduce operational overhead through engineering best practices.
Engineer enterprise networking capabilities including Shared VPC, Private Service Connect, VPC Service Controls, Cloud NAT, firewall policies, segmentation, Cloud Interconnect, and High Availability VPN.
Partner with Information Security to implement zero-trust cloud security including least privilege access, Workload Identity Federation, Binary Authorization, encryption, secrets management, audit logging, and data protection controls.
Integrate Security Command Center, CSPM tooling, automated compliance, monitoring, alerting, tracing, and reliability engineering practices into the cloud platform.
Build self-service platform capabilities that enable product, data, and AI engineering teams to rapidly consume cloud services while maintaining enterprise governance.
Embed FinOps practices including cost attribution, budgeting, rightsizing, committed use planning, tagging standards, and cloud cost optimization.
Engineer the Google Cloud foundation supporting GXO's Enterprise AI Platform, including GKE-based runtimes, AI gateways, model services, agent runtimes, MCP servers, Agent Registry, and governed Snowflake integrations.
Partner with Data Engineering, Security, and Enterprise Architecture to deliver secure AI infrastructure supporting inference, agent execution, identity passthrough, and end-to-end traceability.
Serve as a senior hands-on engineer by writing Terraform, reviewing pull requests, troubleshooting complex cloud issues, mentoring engineers, and raising engineering standards across the organization.