Remote Azure AI Engineer — End-to-End Deployment

ZainTECH; United States; Remote; USD 130,000 - 190,000; Full time

Job summary

ZainTECH is seeking an Azure AI Engineer to deliver enterprise AI on the Azure Stack. You will own the deployment lifecycle, build robust AI services, and ensure compliance with security and governance standards.

Responsibilities include implementing AI solutions, creating RAG pipelines, deploying models to AML/Foundry/AKS, and integrating services via APIs. Collaborate with architects, data engineers, and security teams to deliver scalable, observable AI workloads.

Qualifications

• Hands-on experience with Azure AI Foundry and Azure OpenAI.
• Strong Python skills and REST API experience.
• 2+ years building or deploying AI/data solutions on Azure.
• Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
• Preferred certifications: AI Engineer, Data Engineer, or Solutions Architect.

Responsibilities

• Implement AI solutions on Azure AI Foundry, including agent design, model selection, prompts, and deployment.
• Build RAG pipelines using Azure AI Search, Azure OpenAI, and vector stores; integrate with Data Lake and Databricks.
• Deploy models to Azure ML, Foundry, AKS, and Container Apps; manage endpoint scaling and versioning.
• Integrate AI services with downstream apps via REST APIs, Azure API Management, Logic Apps, and Function Apps.
• Own end-to-end deployment lifecycle, from environment provisioning to go-live and handover.

Skills

Azure AI Foundry

Azure OpenAI

Azure Databricks

Azure Data Lake

Python

REST APIs

Terraform

GitHub Actions

AKS/Container Apps

Azure Monitor

Education

Bachelor's degree in Computer Science/Engineering/Data Science

Tools

Azure DevOps

GitHub Actions

Docker

Azure API Management

Job description

ZainTECH is seeking an Azure AI Engineer to deliver enterprise AI on the Azure Stack. You will own the deployment lifecycle, build robust AI services, and ensure compliance with security and governance standards.

Responsibilities include implementing AI solutions, creating RAG pipelines, deploying models to AML/Foundry/AKS, and integrating services via APIs. Collaborate with architects, data engineers, and security teams to deliver scalable, observable AI workloads.