AI DevOps Engineer

Description
We are looking for an AI DevOps Engineer to help build and scale secure, production-ready AI platform capabilities in Jacksonville, Florida. This Long-term Contract position focuses on enabling application teams with reliable Azure-based infrastructure, automation, and deployment practices for AI services and related workloads. The role will work across platform engineering, security, and development teams to create governed, observable, and maintainable solutions that support enterprise adoption of modern AI technologies.

Responsibilities

Create, deploy, and support Azure-based AI platform services, including search, model access, and related cloud resources, while enabling teams to run workloads within their own subscriptions and resource groups. Establish and manage Azure API Management as the controlled entry point for AI endpoints, applying standards for access control, rate limiting, logging, and consumption visibility. Develop hosting approaches for AI-powered applications and agent services using Azure Container Apps, Azure Functions, and other cloud-native Azure services.

Build and maintain reusable Terraform modules to standardize infrastructure provisioning and improve consistency across environments. Streamline operational tasks through automation for activities such as environment onboarding, access setup, service configuration, and deployment workflows. Design, implement, and support CI/CD pipelines in GitHub Actions and Azure DevOps for infrastructure delivery, platform updates, and AI application releases.

Write and maintain automation and integration code in C# or Python, along with scripting in PowerShell or Bash, to support platform tooling and service operations. Apply Azure security and governance controls, including identity integration, role-based access, secrets management, network restrictions, and approved model guardrails. Implement monitoring and telemetry using Azure Monitor, Application Insights, Log Analytics, and OpenTelemetry to improve reliability, troubleshooting, and cost transparency for AI workloads.

Investigate and resolve infrastructure, deployment, and runtime issues while producing documentation, reference architectures, and runbooks that help other teams adopt the platform effectively. Requirements
3-5 years of experience in DevOps, cloud engineering, or platform engineering roles. Hands-on experience with Microsoft Azure services across compute, networking, storage, and identity management. Practical knowledge of Azure security and authentication methods, including managed identities, Microsoft Entra ID, RBAC, and Key Vault.

Experience creating and maintaining CI/CD pipelines using Azure DevOps and/or GitHub Actions. Proficiency in Terraform for infrastructure as code and automation of cloud resources. Programming experience in C# preferred or Python, plus scripting skills with PowerShell or Bash. Familiarity with containers and cloud platform tooling such as Azure Container Apps, Kubernetes, Docker, or AKS. Understanding of AI platform concepts such as large language models, retrieval-augmented generation, AI agents, Azure AI services, Azure API Management, and MCP servers.

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