.NET & Azure Architect: DevOps + AI Foundations

Machine Learning Technologies, LLC

Charlotte (NC)

On-site

USD 88,000 - 125,000

Full time

Just now
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Job summary

Machine Learning Technologies, LLC seeks an experienced .NET/Azure Architect with DevOps and AI fundamentals to design and modernize cloud-native applications in Charlotte, NC. The role emphasizes CI/CD automation and Terraform IaC, with exposure to AI-assisted software engineering and GenAI concepts.

Responsibilities include designing scalable solutions, implementing REST APIs and microservices, and ensuring robust deployment pipelines.

Qualifications

  • Experience as a .NET/Azure Architect focusing on cloud-native modernization.
  • Proficient in CI/CD automation and Infrastructure as Code using Terraform.
  • Familiarity with AI-enabled software development, GenAI, and related tooling.

Responsibilities

  • Design, develop, and maintain scalable .NET applications using C#, .NET Core, and ASP.NET Core.
  • Build and integrate REST APIs and microservices; apply SOLID, DI, patterns, and clean architecture.
  • Design solutions for scalability, performance, resilience, and maintainability; participate in code reviews and production support.
  • Lead CI/CD pipelines in Azure DevOps; manage YAML pipelines and deployment automation across environments.
  • Incorporate Terraform for Azure provisioning and modularization; ensure secure handling of config and secrets.

Skills

DevOps
Cloud architecture
AI fundamentals
CI/CD practices

Tools

Terraform
Azure
AKS
App Services
Functions
APIM
Service Bus
Event Hubs
Key Vault
Azure SQL
Azure Monitor

Job description

Machine Learning Technologies, LLC seeks an experienced .NET/Azure Architect with DevOps and AI fundamentals to design and modernize cloud-native applications in Charlotte, NC. The role emphasizes CI/CD automation and Terraform IaC, with exposure to AI-assisted software engineering and GenAI concepts.

Responsibilities include designing scalable solutions, implementing REST APIs and microservices, and ensuring robust deployment pipelines.

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