Senior IT & Azure DevOps Engineer

The Aes Group, Inc
Woburn, MA, United States
7 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Application Performance Management Application Services Microsoft Azure Cloud Computing Cloud Computing Security Cloud Engineering Databases Continuous Integration Data as a Services DevOps Domain Name System (DNS)
+33 more
Identity and Access Management Subnetting Python (Programming Language) Key Management Log Analysis Routing OAuth OpenID Peering Windows PowerShell Role-Based Access Control Reliability Engineering OpenAI YAML Enterprise Search Cloud Platform System Cloud Monitoring Spring Cloud Retrieval-Augmented Generation Generative AI Firewalls (Computer Science) Infrastructure as Code (IaC) Git Microsoft Fabric Containerization AI Platforms Git Flow Bicep Terraform Devsecops Api Management Key Vault Static Application Security Testing

Job description

We are seeking a hands-on Senior IT & Azure DevOps Engineer / AI Platform Engineer to build, automate, secure, and operate enterprise Azure platforms supporting Generative AI, cloud-native applications, data services, and Microsoft Fabric/OneLake workloads. This is a platform engineering role focused on Infrastructure as Code (IaC), CI/CD automation, DevSecOps controls, cloud networking, identity, observability, governance, and production readiness across Development, Test, and Production environments., * Engineer Azure landing-zone components, including subscriptions, resource groups, VNets, subnets, NSGs, private endpoints, private DNS, routing, peering, firewall integration, identity boundaries, naming standards, tagging, and environment isolation.

  • Build and maintain Terraform-based Infrastructure as Code modules and Azure DevOps YAML pipelines for repeatable provisioning, automated validation, approvals, artifact promotion, release gates, rollback, and controlled deployments across multiple environments.
  • Deploy and integrate Azure AI Foundry, Azure OpenAI, Azure AI Search, API Management, Key Vault, Storage, managed databases, Microsoft Fabric/OneLake, Purview, and Retrieval-Augmented Generation (RAG) patterns using secure private connectivity and governed access models.
  • Implement DevSecOps controls, including least-privilege RBAC, Managed Identity, App Registrations, OAuth/OIDC, Key Vault secret management, secure pipeline variables, SAST, dependency scanning, IaC scanning, secret scanning, vulnerability gates, and production change controls.
  • Operate platform observability and governance using Azure Monitor, Application Insights, Log Analytics, alerts, dashboards, Azure Policy, cost/quota monitoring, runbooks, architecture diagrams, operational documentation, and audit-ready evidence.

Requirements

  • 5+ years of experience in Cloud Engineering, DevOps, DevSecOps, SRE, or Platform Engineering.
  • 3+ years of hands-on Azure delivery experience in production environments.
  • Strong hands-on experience with Terraform, Azure DevOps, Git, YAML pipelines, Azure networking, Entra ID, Azure RBAC, Key Vault, private endpoints, Azure Monitor, and Log Analytics.
  • Proven experience implementing secure multi-environment deployment practices.
  • Demonstrated ability to troubleshoot complex cloud platform issues.
  • Ability to collaborate across application, cybersecurity, network, data, architecture, and governance teams.
  • Strong technical documentation skills supporting production operations., * Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, and Retrieval-Augmented Generation (RAG).
  • Experience with Microsoft Fabric, OneLake, Microsoft Purview, and API Management.
  • Knowledge of AKS, Azure App Services, GitOps, Azure Policy, and Bicep.
  • Proficiency in PowerShell, Python, and containerization technologies.
  • Familiarity with enterprise AI governance and cloud security best practices.
  • Experience in regulated industries such as banking, financial services, healthcare, or government.
  • Microsoft certifications such as AZ-104, AZ-305, AZ-400, AZ-500, AI-102, or AI-900 are a plus.

Strong candidates should be able to explain how they would securely deploy a Generative AI or RAG workload through Development, Test, and Production environments, addressing:

  • Network isolation and private connectivity
  • Identity and access management
  • Infrastructure as Code using Terraform
  • CI/CD automation and controlled deployments
  • Secrets management and DevSecOps controls
  • Monitoring, observability, and governance
  • Release gates, rollback, and operational support

The ideal candidate is a hands-on Azure DevOps / Platform Engineer with deep Terraform, CI/CD, networking, security, and production operations expertise.

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