GCP Platform Engineer

GCP Platform Engineer – Enterprise Cloud & AI Platform

Location: NYC NY (3 days a week Hybrid role) (Local candidate preffered) 
Role Summary
The GCP Platform Engineer is responsible for designing, building, and operating secure, compliant, and scalable cloud and AI-enabled platforms on Google Cloud Platform (GCP). This role enables application, data, and analytics teams by providing standardized cloud infrastructure, Kubernetes platforms, and approved Google AI services while meeting financial services regulatory, security, and resiliency requirements.
The engineer partners with the Cloud, Data & AI teams, Information Security, and Risk to ensure AI workloads are deployed with appropriate governance, data controls, and observability.
Key Responsibilities
Enterprise Cloud & AI Platform
Design and maintain enterprise GCP landing zones aligned with NYL governance standards.
Build and operate shared cloud services supporting both AI and non-AI workloads.
Implement Infrastructure as Code (Terraform) for platform, networking, and AI service enablement.
Support hybrid connectivity and secure data access patterns for AI use cases.
Kubernetes, Containers & AI Workloads
Engineer and operate GKE clusters for application and AI inference workloads.
Enable containerized AI services and microservices using approved base images.
Support GPU-enabled workloads where approved.
Implement standardized deployment patterns for AI APIs and services.
Google AI / GenAI Enablement Experience: 10+ years of experience in cloud, platform, or DevOps engineering.
GCP Expertise: Strong hands-on experience with Google Cloud Platform.
IaC: Expertise in Terraform and Infrastructure as Code. Harness IACM
Containers: Experience operating Kubernetes / GKE Autopilot in enterprise environments.
Scripting: Proficiency in Python, Bash, or Go.
Security & Networking: Strong understanding of cloud security, IAM, and networking concepts.
Governance: Experience working in regulated or highly governed environments.
Desired / Preferred Qualifications (AI-Focused)
Experience enabling or operating Google AI services, such as:
Vertex AI (endpoints, pipelines, monitoring, agentic AI engines, and communication protocols).
Gemini APIs or other managed GenAI services

 

GCP Platform Engineer – Enterprise Cloud & AI Platform

Location: NYC NY (3 days a week Hybrid role) (Local candidate preffered) 
Role Summary
The GCP Platform Engineer is responsible for designing, building, and operating secure, compliant, and scalable cloud and AI-enabled platforms on Google Cloud Platform (GCP). This role enables application, data, and analytics teams by providing standardized cloud infrastructure, Kubernetes platforms, and approved Google AI services while meeting financial services regulatory, security, and resiliency requirements.
The engineer partners with the Cloud, Data & AI teams, Information Security, and Risk to ensure AI workloads are deployed with appropriate governance, data controls, and observability.
Key Responsibilities
Enterprise Cloud & AI Platform
Design and maintain enterprise GCP landing zones aligned with NYL governance standards.
Build and operate shared cloud services supporting both AI and non-AI workloads.
Implement Infrastructure as Code (Terraform) for platform, networking, and AI service enablement.
Support hybrid connectivity and secure data access patterns for AI use cases.
Kubernetes, Containers & AI Workloads
Engineer and operate GKE clusters for application and AI inference workloads.
Enable containerized AI services and microservices using approved base images.
Support GPU-enabled workloads where approved.
Implement standardized deployment patterns for AI APIs and services.
Google AI / GenAI Enablement Experience: 10+ years of experience in cloud, platform, or DevOps engineering.
GCP Expertise: Strong hands-on experience with Google Cloud Platform.
IaC: Expertise in Terraform and Infrastructure as Code. Harness IACM
Containers: Experience operating Kubernetes / GKE Autopilot in enterprise environments.
Scripting: Proficiency in Python, Bash, or Go.
Security & Networking: Strong understanding of cloud security, IAM, and networking concepts.
Governance: Experience working in regulated or highly governed environments.
Desired / Preferred Qualifications (AI-Focused)
Experience enabling or operating Google AI services, such as:
Vertex AI (endpoints, pipelines, monitoring, agentic AI engines, and communication protocols).
Gemini APIs or other managed GenAI services

 

Job SummaryJob number: CREQ266034Profession: OtherExperience: 5