Senior Cloud Engineer (Cloud & AI Infrastructure)
Plano TX (Onsite) Local only
Onsite Only NO REMOTE OPTION
Job Description:
We are seeking a Senior DevOps Engineer to lead the technical implementation of our Azure Enterprise Landing Zones and AI-ready infrastructure. You will bridge the gap between core cloud architecture and MLOps ensuring that our AI/ML workloads-from Azure OpenAI to custom models-are deployed onto a secure high-performance and fully automated foundation.
## Key Responsibilities
1. Azure Architecture & Landing Zones
Landing Zone Implementation: Deploy and manage scalable Azure Landing Zones ensuring enterprise-grade governance subscription organization and resource hierarchy.
Networking & Security: Architect secure Azure Networking (VNet Peerings Private Links Hub-and-Spoke) and implement robust security guardrails via Azure Policy and Azure Active Directory (Entra ID).
2. Containerization & Orchestration
AKS & Kubernetes: Act as the subject matter expert for Azure Kubernetes Service (AKS) managing cluster lifecycles namespaces and pod security policies.
Docker Expert: Build optimize and secure Docker images for microservices and AI model serving.
Helm Mastery: Utilize Helm Charts for consistent version-controlled application deployments.
3. Infrastructure as Code (IaC) & Automation
Terraform Mastery: Develop and maintain modular enterprise-scale Terraform code to ensure & quot;Everything as Code for both IaaS (VMs Network) and PaaS (APIM Event Hubs).
CI/CD Governance: Build and optimize sophisticated pipelines using Azure DevOps and GitHub Actions integrating security scanning and automated testing.
4. AI & MLOps Integration
AI Workloads: Provision and scale infrastructure for Azure Machine Learning and OpenAI services specifically managing GPU node pools and model monitoring.
MLOps Pipelines: Implement deployment workflows for AI models focusing on model performance tracking and automated drift detection.
5. Observability & Operations
Monitoring: Lead environmental instrumentation using Azure Monitor Log Analytics and Application Insights.
FinOps: Monitor and optimize cloud spend with custom cost-tracking and alerting for high-compute AI resources.
## Technical Requirements
6 Years in DevOps/Cloud: Deep experience with Azure IaaS and PaaS.
IaC Specialist: Advanced proficiency in Terraform for multi-region deployments.
K8s Expert: Hands-on experience with Docker Kubernetes (AKS) and ingress controllers.
Automation Lead: Expert in Azure DevOps and/or GitHub Actions for CI/CD.
Networking Guru: Strong understanding of Azure VNet Firewall and Load Balancing.
AI Aware: Exposure to deploying and managing AI/ML workloads on Azure
Senior Cloud Engineer (Cloud & AI Infrastructure) Plano TX (Onsite) Local only Onsite Only NO REMOTE OPTION Job Description: We are seeking a Senior DevOps Engineer to lead the technical implementation of our Azure Enterprise Landing Zones and AI-ready infrastructure. You will bridge the gap be...
Senior Cloud Engineer (Cloud & AI Infrastructure)
Plano TX (Onsite) Local only
Onsite Only NO REMOTE OPTION
Job Description:
We are seeking a Senior DevOps Engineer to lead the technical implementation of our Azure Enterprise Landing Zones and AI-ready infrastructure. You will bridge the gap between core cloud architecture and MLOps ensuring that our AI/ML workloads-from Azure OpenAI to custom models-are deployed onto a secure high-performance and fully automated foundation.
## Key Responsibilities
1. Azure Architecture & Landing Zones
Landing Zone Implementation: Deploy and manage scalable Azure Landing Zones ensuring enterprise-grade governance subscription organization and resource hierarchy.
Networking & Security: Architect secure Azure Networking (VNet Peerings Private Links Hub-and-Spoke) and implement robust security guardrails via Azure Policy and Azure Active Directory (Entra ID).
2. Containerization & Orchestration
AKS & Kubernetes: Act as the subject matter expert for Azure Kubernetes Service (AKS) managing cluster lifecycles namespaces and pod security policies.
Docker Expert: Build optimize and secure Docker images for microservices and AI model serving.
Helm Mastery: Utilize Helm Charts for consistent version-controlled application deployments.
3. Infrastructure as Code (IaC) & Automation
Terraform Mastery: Develop and maintain modular enterprise-scale Terraform code to ensure & quot;Everything as Code for both IaaS (VMs Network) and PaaS (APIM Event Hubs).
CI/CD Governance: Build and optimize sophisticated pipelines using Azure DevOps and GitHub Actions integrating security scanning and automated testing.
4. AI & MLOps Integration
AI Workloads: Provision and scale infrastructure for Azure Machine Learning and OpenAI services specifically managing GPU node pools and model monitoring.
MLOps Pipelines: Implement deployment workflows for AI models focusing on model performance tracking and automated drift detection.
5. Observability & Operations
Monitoring: Lead environmental instrumentation using Azure Monitor Log Analytics and Application Insights.
FinOps: Monitor and optimize cloud spend with custom cost-tracking and alerting for high-compute AI resources.
## Technical Requirements
6 Years in DevOps/Cloud: Deep experience with Azure IaaS and PaaS.
IaC Specialist: Advanced proficiency in Terraform for multi-region deployments.
K8s Expert: Hands-on experience with Docker Kubernetes (AKS) and ingress controllers.
Automation Lead: Expert in Azure DevOps and/or GitHub Actions for CI/CD.
Networking Guru: Strong understanding of Azure VNet Firewall and Load Balancing.
AI Aware: Exposure to deploying and managing AI/ML workloads on Azure
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