Terraform Engineer Azure-Centric

Location: Charlotte NC or Dallas TX

Employment Type: Contract

US Citizens only

We are seeking a highly skilled Senior Terraform Engineer with deep expertise in Azure services to join our Enterprise AI Platform team. This role is Azure-centric with a strong emphasis on deploying Machine Learning (ML) and Generative AI (GenAI) models in scalable secure enterprise environments.

The ideal candidate will have hands-on experience with multi-cloud architectures Infrastructure as Code (IaC) best practices and a strong foundation in ML workflows enterprise AI platforms and cloud-based ML services. You will play a key role in automating infrastructure provisioning integrating AI/ML pipelines and optimizing deployments for performance cost security and compliance across a multi-cloud landscape.

This position requires a proactive engineer who can bridge DevOps and MLOps leveraging Terraform to support high-impact AI initiatives. If you thrive in fast-paced environments and are passionate about building robust automated cloud infrastructures for AI at scale this role offers a unique opportunity to drive innovation.

Key Responsibilities

Infrastructure as Code & Azure Platform Engineering

• Design implement and maintain Infrastructure as Code (IaC) solutions using Terraform to provision and manage Azure resources including:
  

  • Azure Machine Learning (Azure ML)
    

  • Azure AI Studio
    

  • Azure Kubernetes Service (AKS)
    

  • Azure Databricks
    

  • Related services supporting ML and GenAI model deployment
    

• Develop and enforce IaC best practices including:
  

  • Modular Terraform design
    

  • Remote state management (Azure Storage backends)
    

  • Drift detection
    

  • Automated policy and security testing using tools such as Terragrunt and Checkov
    

ML & GenAI Platform Enablement

• Deploy and orchestrate ML and GenAI models on enterprise ML platforms
  

• Enable end-to-end automation across the ML lifecycle from model training through inference
  

• Integrate AI/ML workflows with CI/CD pipelines (Azure DevOps GitHub Actions)
  

Multi-Cloud Architecture & Integration

• Collaborate with data scientists ML engineers and cross-functional teams to design multi-cloud architectures with Azure as the primary platform and AWS/Google Cloud Platform integrations
  

• Support hybrid deployments data sovereignty requirements and disaster recovery strategies
  

• Implement cross-cloud networking identity federation and resource orchestration
  

Cloud Optimization & Security

• Optimize cloud infrastructure for AI/ML workloads including:
  

  • Compute clusters
    

  • Storage (Azure Blob Storage Azure Data Lake Storage ADLS)
    

  • Networking (Virtual Networks Private Endpoints)
    

  • Security controls (Azure RBAC Azure Key Vault Azure Sentinel)
    

• Ensure infrastructure meets enterprise security availability and compliance standards (e.g. GDPR SOC 2)
  

MLOps & Observability

• Implement MLOps best practices including:
  

  • Model versioning
    

  • Monitoring
    

  • Logging
    

  • Alerting
    

• Leverage observability tools such as Azure Monitor Prometheus and MLflow to ensure reliable production-grade deployments
  

Operations & Collaboration

• Troubleshoot and resolve infrastructure issues in production AI environments
  

• Ensure high availability scalability and reliability of AI platforms
  

• Conduct code reviews mentor junior engineers and contribute to documentation for ML/GenAI-specific IaC patterns
  

• Stay current with emerging Azure ML services including:
  

  • Azure OpenAI Service
    

  • Prompt Flow
    

• Participate in on-call rotations and incident response for critical AI infrastructure
  

Required Qualifications

• Bachelors or Masters degree in Computer Science Engineering or a related field (or equivalent professional experience)
  

• 5 years of experience as a Cloud Engineer DevOps Engineer or similar role
  

• At least 3 years of hands-on experience with Terraform for IaC in Azure environments
  

• Proven experience deploying ML and GenAI models using Azure ML including:
  

  • Model training
    

  • Model registration
    

  • Managed endpoints
    

  • Inference pipelines
    

• Strong hands-on experience with multi-cloud architectures
  

  • Azure required
    

  • AWS and/or Google Cloud Platform preferred
    

• In-depth understanding of Terraform concepts including:
  

  • Modules
    

  • Providers (AzureRM)
    

  • Variables and outputs
    

  • Workspaces and backends
    

• Solid understanding of the machine learning lifecycle including:
  

  • Data ingestion
    

  • Feature engineering
    

  • Model serving
    

  • Scaling in enterprise AI platforms (Azure ML SageMaker Vertex AI)
    

• Experience with containerization and orchestration tools:
  

  • Docker
    

  • Kubernetes (AKS)
    

  • Helm
    

• Proficiency in scripting languages such as Python PowerShell or Bash
  

• Familiarity with cloud security best practices for ML environments including:
  

  • Encryption
    

  • Access controls
    

  • Vulnerability scanning
    

• Strong problem-solving skills and experience working in Agile teams
  

Preferred Qualifications

• Relevant certifications including:
  

  • Microsoft Certified: Azure DevOps Engineer Expert
    

  • Azure AI Engineer Associate
    

  • HashiCorp Certified: Terraform Associate
    

• Experience with additional IaC tools such as:
  

  • ARM Templates
    

  • Bicep
    

  • Pulumi (for hybrid Azure setups)
    

• Background in MLOps tooling including:
  

  • Kubeflow
    

  • MLflow
    

  • Azure ML Pipelines
    

• Experience with cloud cost optimization for AI workloads using tools like Azure Cost Management
  

• Prior experience working in regulated industries (finance healthcare etc.) with compliance-driven infrastructure requirements