What are the responsibilities and job description for the Cloud GenAI Platform Engineer (Google Cloud Platform + Azure) – Infrastructure Provisioning & Kubernetes position at VDart, Inc.?
Role: Cloud GenAI Platform Engineer (Google Cloud Platform Azure) – Infrastructure Provisioning & Kubernetes
Location: Charlotte, NC (Onsite)
Type: Contract
Role Summary
- We are seeking a hands-on Cloud GenAI Platform Engineer to support an enterprise GenAI platform enabling predictive and generative AI inferencing across both Google Cloud Platform and Azure. This role is focused on platform/infrastructure provisioning (IaaS/PaaS): creating cloud projects/subscriptions, enabling required services, establishing secure access/entitlements, deploying containerized components, and automating everything through Terraform. This is not an application development or RAG/agent pipeline build role.
- Key Responsibilities (Day-to-Day)
- Cloud Provisioning for GenAI Consumers: Build secure, repeatable cloud environments for internal teams consuming GenAI services (e.g., provisioning Google Cloud Platform projects / Azure resources, enabling notebooks, endpoint access, guardrails, telemetry integrations).
- Infrastructure as Code (Terraform): Author, enhance, and maintain Terraform modules/scripts to automate:
- Cloud project/resource creation
- IAM/entitlements setup and access control
- Network/security baseline configuration
- Enablement of required GenAI platform services
- Containers & Kubernetes Operations: Package, deploy, and troubleshoot containerized services; debug runtime issues, image builds, configuration, and cluster-level behavior.
- Platform Troubleshooting & Support: Rapidly diagnose issues across cloud console/portals, infrastructure configs, IAM, containers, and platform integrations; drive issues to resolution with clear root-cause documentation.
- Cross-Team Provisioning Coordination: Partner with internal platform/security/operations teams to complete environment provisioning and ensure standards are met.
Required Skills / Qualifications
- Strong hands-on experience with both:
- Google Cloud Platform (projects, IAM, service enablement, console navigation)
- Azure (subscriptions/resource groups, IAM/RBAC, portal navigation)
- Proven hands-on experience with:
- Terraform (writing/debugging IaC, modularization, state management basics)
- Containers (Docker/container build & runtime debugging)
- Kubernetes (deployments, services, configmaps/secrets, troubleshooting)
- Strong troubleshooting skills across:
- Cloud access/permissions (IAM/RBAC)
- Container failures, image issues, runtime misconfigurations
- Basic networking and API connectivity patterns
Preferred / Nice-to-Have
- Familiarity with GenAI platform governance/guardrails concepts (e.g., policy enforcement, request/response inspection).
- Exposure to rate limiting / API gateway behaviors and diagnosing throttling patterns.
- Experience in regulated enterprise environments (security-first provisioning).
Experience Level
- Typically, 6–10 years in cloud/platform engineering roles (flexible based on depth of hands-on skills).
Role: Cloud GenAI Platform Engineer (Google Cloud Platform Azure) – Infrastructure Provisioning & Kubernetes
Location: Charlotte, NC (Onsite)
Type: Contract
Role Summary
- We are seeking a hands-on Cloud GenAI Platform Engineer to support an enterprise GenAI platform enabling predictive and generative AI inferencing across both Google Cloud Platform and Azure. This role is focused on platform/infrastructure provisioning (IaaS/PaaS): creating cloud projects/subscriptions, enabling required services, establishing secure access/entitlements, deploying containerized components, and automating everything through Terraform. This is not an application development or RAG/agent pipeline build role.
- Key Responsibilities (Day-to-Day)
- Cloud Provisioning for GenAI Consumers: Build secure, repeatable cloud environments for internal teams consuming GenAI services (e.g., provisioning Google Cloud Platform projects / Azure resources, enabling notebooks, endpoint access, guardrails, telemetry integrations).
- Infrastructure as Code (Terraform): Author, enhance, and maintain Terraform modules/scripts to automate:
- Cloud project/resource creation
- IAM/entitlements setup and access control
- Network/security baseline configuration
- Enablement of required GenAI platform services
- Containers & Kubernetes Operations: Package, deploy, and troubleshoot containerized services; debug runtime issues, image builds, configuration, and cluster-level behavior.
- Platform Troubleshooting & Support: Rapidly diagnose issues across cloud console/portals, infrastructure configs, IAM, containers, and platform integrations; drive issues to resolution with clear root-cause documentation.
- Cross-Team Provisioning Coordination: Partner with internal platform/security/operations teams to complete environment provisioning and ensure standards are met.
Required Skills / Qualifications
- Strong hands-on experience with both:
- Google Cloud Platform (projects, IAM, service enablement, console navigation)
- Azure (subscriptions/resource groups, IAM/RBAC, portal navigation)
- Proven hands-on experience with:
- Terraform (writing/debugging IaC, modularization, state management basics)
- Containers (Docker/container build & runtime debugging)
- Kubernetes (deployments, services, configmaps/secrets, troubleshooting)
- Strong troubleshooting skills across:
- Cloud access/permissions (IAM/RBAC)
- Container failures, image issues, runtime misconfigurations
- Basic networking and API connectivity patterns
Preferred / Nice-to-Have
- Familiarity with GenAI platform governance/guardrails concepts (e.g., policy enforcement, request/response inspection).
- Exposure to rate limiting / API gateway behaviors and diagnosing throttling patterns.
- Experience in regulated enterprise environments (security-first provisioning).
Experience Level
- Typically, 6–10 years in cloud/platform engineering roles (flexible based on depth of hands-on skills).