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Job Summary
We are seeking an Azure Platform Engineer to design, build, and operate the Azure infrastructure supporting a next-generation revenue cycle management (RCM) platform and an AI-powered medical coding product.
This individual will work closely with an AI Architect to translate architecture into secure, HIPAA-compliant production infrastructure. You will also provide the environments and services needed for a Data Integration Engineer to migrate data from legacy practice management and RCM systems.
This is a hands-on role with ownership across Azure landing zones, networking, compute, data and AI services, CI/CD, security, observability, and reliability. All infrastructure must be defined and maintained through code, with repeatable deployments and controlled changes.
You will use AI tools regularly to accelerate infrastructure development, automation, pipelines, and documentation while reviewing and validating their output before production use.
Key Responsibilities
• Azure foundation: Build and maintain landing zones, management groups, subscriptions, role-based access control, Azure Policy, hub-and-spoke networking, private endpoints, and DNS.
• Infrastructure as code: Define development, test, and production environments using Terraform or Bicep, including reusable modules, state management, and drift detection. Maintain infrastructure through code rather than manual portal changes.
• AI infrastructure: Provision and operate Azure OpenAI, Azure AI Foundry, Azure AI Search, and model endpoints. Manage quotas, capacity, private networking, content filtering, token usage, latency, and error rates.
• Application hosting: Deploy and operate containerized services using AKS and/or Azure Container Apps, with App Service and Azure Functions where appropriate. Manage internal and partner APIs through Azure API Management.
• Data infrastructure: Build and secure Azure SQL, Data Lake Storage, Data Factory and/or Fabric, Service Bus, and Event Grid environments supporting data integration and legacy system migrations.
• CI/CD: Develop Azure DevOps or GitHub Actions pipelines for infrastructure and application deployments, including environment promotion, approval gates, and rollback processes.
• Security and compliance: Implement infrastructure controls supporting HIPAA and protected health information (PHI) requirements. Manage Entra ID, managed identities, Key Vault, encryption, Defender for Cloud, and audit logging needed for SOC 2 and HITRUST evidence.
• Reliability: Build monitoring and alerting using Azure Monitor, Log Analytics, and Application Insights. Define and test backup, disaster recovery, recovery time objectives, and recovery point objectives. Participate in on-call support and incident response.
• Cost management: Establish resource tagging, budgets, cost reporting, and compute optimization. Monitor Azure OpenAI consumption and manage platform spending.
• Collaboration: Work closely with the AI Architect and Data Integration Engineer to implement architecture, support migrations, and identify designs that require changes before production deployment.
• Documentation: Maintain architecture diagrams, runbooks, and environment standards that support consistent operations across the engineering team.
Qualifications
Experience
• Minimum of 5 years of experience in cloud infrastructure, platform engineering, or DevOps, including at least 3 years building and operating production workloads on Azure.
• Demonstrated ownership of a production environment across deployment, security, monitoring, reliability, and ongoing operations.
• Experience in healthcare or another regulated industry involving HIPAA, SOC 2, HITRUST, or PCI requirements is strongly preferred.
Technical Requirements
• Strong Azure networking, identity, and governance experience, including VNets, private endpoints, NSGs, Azure Firewall, Front Door, Entra ID, managed identities, RBAC, Azure Policy, and management groups.
• Production experience with Terraform and/or Bicep, including reusable modules, remote state, and drift control.
• Hands-on experience deploying and operating Azure OpenAI, Azure AI Foundry, or comparable LLM infrastructure in production, with specific examples of delivered solutions.
• Experience with Docker and AKS or Azure Container Apps.
• CI/CD experience using Azure DevOps Pipelines or GitHub Actions.
• Scripting skills in PowerShell, Bash, and Python.
• Observability experience using Azure Monitor, Log Analytics, KQL, and Application Insights.
• Security experience supporting PHI, including secrets management, Key Vault, Defender for Cloud, and least-privilege access.
• Regular use of AI coding tools, such as GitHub Copilot or Claude, for infrastructure as code and automation, with the ability to review, test, and validate generated output.
Preferred Qualifications
• Experience with Azure SQL, Data Lake Storage, Data Factory, and Microsoft Fabric.
• Azure certifications such as AZ-104, AZ-305, AZ-400, or AZ-500.
