Remote Azure DevOps Engineer for AI Data Platform

CodeRoad; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Health insurance assistance

Paid Holidays off

Generous PTO

100% Remote work flexibility

Career growth opportunities

Job summary

CodeRoad is seeking an Intermediate DevOps Engineer to own Azure infrastructure for a cutting-edge AI platform. You will manage data stores, AI services, and user-facing apps, partnering with AI, data, and backend engineers to build a secure cloud ecosystem.

This role emphasizes security from day one, enabling scalable, compliant AI capabilities and maintaining robust CI/CD, infrastructure as code, and private networking across environments.

Qualifications

• 2–4 years of total DevOps or cloud engineering experience.
• At least 2+ years focused on Azure and cloud infrastructure.
• Hands-on with Terraform or Bicep and container hosting on Azure services.
• Scripting in Python or Bash and strong security awareness in CI/CD.

Responsibilities

• Provision and manage end-to-end Azure infrastructure as code.
• Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions.
• Optimize data layer with relational databases, object storage, and vector databases.
• Lead security and secrets management with Azure Key Vault and RBAC.
• Deploy and containerize Python services and AI tooling.
• Collaborate with PODs to enforce network isolation and secure CI/CD.

Skills

Ownership mindset

Proactive problem-solving

Team collaboration

Advanced English

Tools

Terraform

Bicep

Azure Container Apps

AKS

App Service

Python

Bash

Azure DevOps

GitHub Actions

Azure SQL

Blob Storage

Azure Key Vault

Azure RBAC

Job description

CodeRoad is seeking an Intermediate DevOps Engineer to own Azure infrastructure for a cutting-edge AI platform. You will manage data stores, AI services, and user-facing apps, partnering with AI, data, and backend engineers to build a secure cloud ecosystem.

This role emphasizes security from day one, enabling scalable, compliant AI capabilities and maintaining robust CI/CD, infrastructure as code, and private networking across environments.