C

CIVIE

Senior Azure Cloud Infrastructure Engineer - Healthcare AI Platform

Cloud EngineeringUpdated on Nov 11
Full-timeRemote in USANo salary listed

About the Job

Requirements

  • 5–8+ years of hands-on experience with Microsoft Azure cloud infrastructure.
  • Proven experience designing high-availability and disaster recovery systems in regulated environments.
  • A strong background in healthcare or other compliance-heavy industries.
  • Deep expertise in Azure Virtual Machines, VM Scale Sets, and GPU compute.
  • Expertise in Azure networking, including VNets, Private Link, ExpressRoute, and firewalls.
  • Expertise in storage solutions, including Blob, Files, and managed disks with redundancy options.
  • Experience implementing compliance frameworks such as HIPAA or SOC 2.
  • Strong knowledge of identity and access control, including RBAC, Azure AD, and managed identities.
  • Experience with Kubernetes (AKS) and containerized workloads.
  • Proficiency in scripting with Python, Bash, and PowerShell.

Responsibilities

  • Architect and manage highly available, fault-tolerant systems on Microsoft Azure with multi-region redundancy and disaster recovery.
  • Design infrastructure in strict adherence to healthcare compliance standards such as HIPAA, HITRUST, and SOC 2.
  • Provision and optimize GPU-based environments for AI/ML workloads, including large-scale model training and inference.
  • Build secure, zero-trust architectures using private networking, encryption, identity isolation, and least-privilege access.
  • Implement backup, failover, and business continuity strategies with clearly defined RTO/RPO targets.
  • Continuously reduce infrastructure costs through intelligent scaling, reserved capacity, spot instances, and workload optimization.
  • Develop Infrastructure as Code using Terraform, Bicep, and ARM for repeatable, auditable deployments.
  • Partner with AI/ML teams to productionize and scale foundational models reliably.
  • Establish observability across systems through logging, monitoring, and alerting, with proactive incident response.
  • Conduct architecture reviews, risk assessments, and security audits.
  • Build multi-region architecture with automated failover, end-to-end encryption for data at rest and in transit, and segmented development, staging, and production environments with strict isolation.
  • Provide real-time monitoring and alerting with defined SLAs, automated backup and recovery with regular testing, and cost visibility and governance across all resources.

Desired Qualifications

  • Experience with the Azure AI ecosystem, including Azure Machine Learning, Azure AI Foundry, and Cognitive Services.
  • Familiarity with distributed training, model parallelism, and GPU orchestration.
  • Experience implementing MLOps pipelines in regulated environments.
  • Azure certifications such as Solutions Architect Expert, Security Engineer Associate, or DevOps Engineer Expert.
  • Experience with zero-downtime deployments and blue/green or canary strategies.

About the Company

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