Requirement : AI Engineer IV Azure Cloud Infrastructure (w2 position)
Job Title: AI Engineer IV Azure Cloud Infrastructure
Location: Richmond, VA (Hybrid Proof of Residency Required)
Experience Level: Senior / Level IV
Job Summary
We are seeking a highly skilled AI Engineer IV to design, implement, optimize, and maintain Azure cloud infrastructure supporting enterprise-level AI/ML workloads.
This role requires deep expertise in Azure services, Infrastructure as Code (IaC), CI/CD automation, observability, and scalable AI platform engineering.
On-site presence in Richmond, VA is required on designated days.
Key Responsibilities
Azure Cloud Infrastructure
Design and maintain Azure environments supporting AI/ML platforms.
Manage Azure compute, storage, networking, and security services.
Implement Azure services including AKS, Azure ML, ADF, Functions, Service Bus, Key Vault, APIM, VNets, Load Balancers.
AI/ML Platform Support
Deploy and manage AI/ML workloads (training, inference, pipelines).
Ensure reliability, scalability, and performance of AI infrastructure.
Collaborate with Data Scientists and ML Engineers on model deployment and operationalization.
Infrastructure as Code (IaC)
Develop and maintain Terraform/Bicep/ARM templates.
Ensure consistent, secure, and compliant environment provisioning.
Automate infrastructure provisioning workflows.
CI/CD Pipelines
Build and maintain CI/CD pipelines using Azure DevOps / GitHub Actions.
Automate build, test, deployment, and monitoring workflows.
Implement DevSecOps practices including policy checks and vulnerability scanning.
Monitoring & Observability
Implement Azure Monitor, Log Analytics, App Insights, and Grafana-based observability.
Configure metrics, alerts, dashboards, and logging.
Troubleshoot performance issues and perform RCA.
Security, Compliance & Governance
Implement Azure security best practices, RBAC, policies, governance controls.
Ensure compliance with NIST, SOC2, and enterprise standards.
Manage secure deployment, encryption, and access control.
Collaboration & Documentation
Work cross-functionally with Data Science, Security, Cloud Engineering, and Architecture teams.
Document infrastructure, deployment processes, and configuration standards.
Mentor junior engineers and contribute to design discussions.
Required Qualifications
Bachelor's/Master's in Computer Science, Engineering, or equivalent experience.
8 12+ years in cloud engineering or DevOps.
5+ years of hands-on Azure experience.
Strong proficiency with Terraform, Bicep, or ARM.
Proven CI/CD automation expertise (Azure DevOps/GitHub Actions).
Experience supporting AI/ML workloads (Azure ML, AKS, Databricks, etc.).
Strong knowledge of monitoring tools and cloud networking.
Proficiency with Python, PowerShell, or Bash scripting.
Preferred Qualifications
Azure certifications: AZ-305, AZ-400, DP-203, AI-102, etc.
Experience with Kubernetes (AKS) and containerized AI deployments.
Familiarity with MLOps frameworks and ML lifecycle management.
Experience in large enterprise or regulated industries.
Work Arrangement
Hybrid role Richmond, VA.
Proof of residency required.
On-site attendance 2 3 days/week (per client schedule).
Thanks& Regards,
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