Senior Azure Cloud Infrastructure Engineer; Healthcare AI Platform

Overview

We’relooking fora Senior Azure Cloud Infrastructure Engineer to design, build, andoperatea highly resilient, secure, and cost-efficient cloud platform supporting advanced AI workloads in a healthcare environment.

This roleis responsible for mission-critical infrastructure powering our proprietary foundational AI model, including GPU-based compute, while meeting strict requirements for compliance, data protection, and high availability. You will play a key role in ensuring our systems are fault-tolerant, auditable, and continuouslyoptimizedfor both performance and cost.

• Architect and manage highly available, fault-tolerant systems on Microsoft Azure with multi-region redundancy and disaster recovery
• Design infrastructure with strict adherence to healthcare compliance standards (e.g., HIPAA, HITRUST, SOC
  2)
• Provision andoptimizeGPU-based environments for AI/ML workloads, including large-scale model training and inference
• Build secure, zero-trust architectures (private networking, encryption, identity isolation, 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 (Terraform, Bicep, ARM) for repeatable, auditable deployments
• Partner with AI/ML teams to product ionize and scale foundational models reliably
• Establish observability across systems (logging, monitoring, alerting) with proactive incident response
• Conduct architecture reviews, risk assessments, and security audits

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

• Experience with Azure AI ecosystem (Azure Machine Learning, Azure AI Foundry, Cognitive Services)
• Familiarity with distributed training, model parallelism, and GPU orchestration
• Experience implementingMLOpspipelines in regulated environments
• Azure certifications (Solutions Architect Expert, Security Engineer Associate, Dev Ops Engineer Expert)
• Experience with zero-downtime deployments and blue/green or canary strategies

• Multi-region architecture with automated failover
• End-to-end encryption (data at rest and in transit)
• Segmented environments (dev/staging/prod) with strict isolation
• Real-time monitoring and alerting with defined SLAs
• Automated backup and recovery with regular testing
• Cost visibility and governance across all resources

• Near-zero downtime systems with tested failover capabilities
• Full compliance readiness with audit trails and documentation
• Efficient GPUutilizationsupporting AI workloads at scale
• Measurable reduction in cloudspendwithout compromising reliability or security
• Seamless collaboration between infrastructure and AI teams

You will be building the backbone of the next-generation healthcare AI platform - where reliability, security, and performance directly impact real-world outcomes. This is not just infrastructure; it is critical systems engineering at the…