Description

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

Key Skills

Education

Bachelor's degree