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Cloud Architect (AZURE

Job in Cincinnati, Hamilton County, Ohio, 45208, USA
Listing for: CBTS
Full Time position
Listed on 2026-08-22
Job specializations:
  • IT/Tech
    Cloud Computing: Infrastructure & Operations, Azure, Systems Engineer
Salary/Wage Range or Industry Benchmark: 140000 - 200000 USD Yearly USD 140000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: Cloud Architect (AZURE)

About the Environment

Veritiv Corporation is a leading North American distribution company running a large, complex Azure environment shaped by significant M&A activity — seven acquired entities, multiple inherited application portfolios, and a mandate to modernize. This role sits on the application side of the house, not infrastructure. You will be designing, governing, and modernizing the way applications are built and run in Azure — working closely with development teams, data engineering, and business stakeholders.

You will also play a hands‑on role in establishing standards, guiding deployments, and enforcing application security across the environment.

What You’ll Do
  • Own Azure application architecture across a complex, post‑M&A environment — assessing the current application portfolio and defining a target‑state modernization roadmap
  • Design cloud‑native architectures using Azure PaaS services — App Services, Azure Functions, API Management, Service Bus, Event Grid, and Logic Apps
  • Establish and govern application design patterns — microservices, event‑driven architecture, API‑first, and containerized workloads — and ensure consistency across development teams
  • Define integration architecture across internal systems, acquired‑entity applications, and external partners
  • Lead application rationalization decisions across the inherited M&A portfolio — consolidate, retire, rebuild, or retain
  • Architect and govern containerization strategy across the Azure environment — defining standards for image management, container security, and registry governance via Azure Container Registry (ACR)
  • Design and manage Azure Kubernetes Service (AKS) clusters — including node pool design, autoscaling, namespace strategy, network policies, and workload scheduling
  • Implement Kubernetes orchestration patterns for microservices deployments — Helm charts, Kustomize, pod disruption budgets, and horizontal pod autoscaling
  • Define and enforce container security standards — image scanning, runtime policies, and secrets management via Azure Key Vault integration
  • Evaluate and implement Azure Container Apps where appropriate as a managed orchestration alternative to full AKS
Infrastructure as Code & Git Ops
  • Define and enforce IaC standards using Terraform — every environment must be version‑controlled, repeatable, and peer‑reviewed before deployment
  • Establish Git Ops workflows using Git (Git Hub or Azure Repos) as the single source of truth for application and infrastructure state
  • Implement branch strategy, PR review gates, and policy enforcement as part of the deployment pipeline
  • Govern environment promotion (dev → staging → production) through pipeline‑enforced controls, not manual processes
  • Integrate Terraform state management, module strategy, and drift detection into standard operating procedure
CI/CD & Deployment Standards
  • Design and govern CI/CD pipeline standards using Azure Dev Ops and/or Git Hub Actions — covering build, test, security scan, and release stages
  • Establish deployment standards across the application portfolio — blue/green, canary, and rolling deployment patterns where appropriate
  • Define and enforce pipeline security gates — static code analysis, dependency scanning, container image scanning, and secrets detection before any artifact reaches production
  • Partner with development teams to adopt and maintain deployment standards consistently across teams and business units
AI‑Assisted Development with Claude
  • Integrate Claude (Anthropic) into the development workflow as an AI coding and architecture assistant — establishing standards for responsible and effective use across engineering teams
  • Define guardrails for AI‑assisted code generation — review requirements, security considerations, and quality gates before AI‑generated code reaches production
  • Champion the use of AI tooling to accelerate development velocity while maintaining code quality and security standards
  • Stay current on Claude and broader AI coding assistant capabilities as they evolve, and advise leadership on adoption opportunities
Application Security
  • Embed security into every layer of the application architecture — this is not a handoff to a security team, it is a…
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