> Markdown version of [/jobs/ext/3080864-senior-azure-devsecops-cloud-platform-engineer](https://www.wearedevelopers.com/jobs/ext/3080864-senior-azure-devsecops-cloud-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

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# Senior Azure DevSecOps Cloud Platform Engineer

- **Company:** Bridgetown Consulting Group
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $83,200.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Computing Security, Continuous Integration, Linux, Github, Identity and Access Management, Network Security, Role-Based Access Control, Security Software, Azure Service Bus, Cloud Platform System, Large Language Models, Generative AI, Event Driven Architecture, Containerization, AI Platforms, Google Cloud Functions, Bicep, Terraform, Devsecops, Serverless Computing, Microservices
- **Published:** September 25, 2026
- **Apply:** https://www.dice.com/job-detail/56d5bf92-4768-4392-b1d1-c29999b425a0

## About the Role

* 5+ years of hands-on experience with Microsoft Azure
 * Strong experience with Terraform
 * Experience with Bicep/ARM Templates
 * Strong hands-on experience with GitHub Actions
 * Experience with self-hosted Linux runners
 * Strong CI/CD and DevSecOps experience
 * Experience with Azure Container Apps (ACA)
 * Experience with Azure Container Registry (ACR)
 * Experience with Azure Function Apps
 * Experience with Azure App Service Plans
 * Strong knowledge of Azure-native services
 * Experience with Azure Event Grid
 * Experience with Azure Service Bus
 * Strong knowledge of Azure RBAC/IAM
 * Experience with User-Assigned Managed Identities
 * Experience with Private Endpoints and secure network routing
 * Experience with microservices and containerized APIs
 * Experience with reverse proxies and event-driven architectures

AI / GenAI Experience

 * Experience supporting AI/ML or Generative AI infrastructure
 * Experience with Azure OpenAI
 * Exposure to Gemini and Claude LLM endpoints
 * Experience with LLM endpoint deployment and management
 * Understanding of AI token consumption, metering, and related infrastructure
 * Experience supporting enterprise AI/LLM platforms is highly preferred, * Enterprise-scale Azure environment experience
 * Production-grade DevSecOps experience
 * AI/LLM platform engineering experience
 * Azure OpenAI integration experience
 * Experience with automated security and compliance controls
 * Strong understanding of cloud security and governance
 * AZ-400 certification preferred

## Description

Our client, a large Accounting & Technology firm, is urgently looking for a Senior Azure DevSecOps Cloud Platform Engineer to support and scale enterprise Azure infrastructure and AI platform services.

The ideal candidate should have strong hands-on experience with Azure Cloud, DevSecOps, Terraform, GitHub Actions, CI/CD, containerized applications, microservices, and AI/LLM infrastructure.

The candidate will be responsible for designing, provisioning, deploying, automating, and maintaining Azure infrastructure, including Azure Container Apps, Azure Container Registry, Azure Functions, event-driven services, secure networking, and AI/LLM endpoints., * Design and maintain modular Terraform/Bicep configurations

 * Automate Azure infrastructure provisioning and deployment
 * Build and maintain enterprise CI/CD pipelines
 * Develop GitHub Actions workflows for build, deployment, release, and validation
 * Support self-hosted Linux runners
 * Deploy and manage containerized applications and microservices
 * Work extensively with Azure Container Apps and Azure Container Registry
 * Configure Azure Event Grid, Service Bus, and Event Subscriptions
 * Implement Azure RBAC/IAM and managed identities
 * Configure secure secret management
 * Troubleshoot private endpoint routing and Azure networking
 * Support enterprise AI/LLM platform infrastructure
 * Implement production-grade DevSecOps, security, governance, and automation
 * Support highly available and scalable Azure cloud environments


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