GCP Engineer with AI

Role: GCP Platform Engineer – Enterprise Cloud & AI Platform

Type: Contract

Location: NYC, New York - Hybrid

Job Summar

yWe are seeking an experienced GCP Platform Enginee r to design, build, and operate secure, scalable, and compliant cloud platforms on Google Cloud Platform (GCP ). The ideal candidate will enable enterprise application, data, analytics, and AI teams by delivering standardized cloud infrastructure, Kubernetes platforms, and Google AI services while ensuring compliance with security, governance, and resiliency standards

.This role partners closely with Cloud Engineering, Data & AI, Information Security, Risk, and DevOps team s to deploy AI workloads with appropriate governance, observability, and data protection controls in highly regulated enterprise environments

.Key Responsibilities

:Enterprise Cloud Platfor

• mDesign, implement, and maintain enterprise GCP landing zones aligned with organizational cloud governance standards
• .Build and operate secure, scalable cloud platforms supporting both AI and traditional enterprise workloads
• .Develop reusable Infrastructure as Code (IaC) modules using Terrafor m and Harness Infrastructure as Code Management (IACM )
• .Implement enterprise networking, identity, and shared cloud services
• .Support hybrid cloud connectivity and secure data access architectures
• .Ensure platform availability, resiliency, disaster recovery, and operational excellence

.Kubernetes & Container Platfor

• mDesign, deploy, and manage Google Kubernetes Engine (GKE ) clusters, including GKE Autopilo t
• .Build and maintain enterprise container platforms for microservices and AI inference workloads
• .Implement standardized deployment patterns for containerized applications and AI services
• .Support GPU-enabled infrastructure for approved AI and machine learning workloads
• .Optimize Kubernetes performance, scalability, monitoring, and resource utilization

.Google AI & Generative AI Platfor

• mEnable and operate Google Cloud AI services for enterprise AI initiatives
• .Deploy and manage Vertex A I services, including
• :Model Endpoint
• sPipeline
• sModel Monitorin
• gAgentic AI Engine
• sCommunication Protocol
• sIntegrate Gemini API s and other managed Generative AI services into enterprise platforms
• .Support secure AI model deployment, inference infrastructure, and AI service lifecycle management
• .Collaborate with Data Science and AI Engineering teams to operationalize machine learning solutions

.Security, Governance & Complianc

• eImplement cloud security best practices across GCP environments
• .Configure IAM, network security, encryption, secrets management, and policy enforcement
• .Ensure compliance with enterprise governance, regulatory, and financial services security standards
• .Implement logging, monitoring, observability, and audit controls across cloud platforms
• .Partner with Information Security and Risk teams to enforce cloud governance policies

.Automation & DevOp

• sAutomate cloud provisioning, deployment, and platform operations
• .Build and maintain CI/CD pipelines supporting cloud infrastructure and application deployments
• .Develop automation scripts using Pytho n, Bas h, or G o
• .Monitor platform health and proactively optimize infrastructure performance and cost

**.

Required Qualificatio**

• nsBachelor’s degree i n Computer Science, Information Technology, Engineeri ng, or a related fiel
• d.10+ yea rs of experience in Cloud Engineering, Platform Engineering, Infrastructure Engineering, or DevOp
• s.Strong hands-on experience designing and operating enterprise cloud platforms o n Google Cloud Platform (GC P
• ).Experience working in highly regulated enterprise environments such as financial services, healthcare, or insuranc

e.