AI Infrastructure Engineer

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

Job summary

The AI Office is seeking an AI Infrastructure Engineer to own the reliability of an Azure-based AI and analytics platform, and to operationalize AI solutions into production. You will bridge cloud infrastructure, DevOps, MLOps, and AIOps to keep production data and model pipelines running while provisioning and deploying environments for new AI use cases.

Responsibilities include managing platform operations (50%), deployment and containerization (25%), and collaborating with enterprise IT,

Qualifications

• Experience in DevOps, cloud infrastructure, or MLOps roles.
• Proficiency with IaC and Azure services.
• Hands-on with Docker and CI/CD pipelines.
• Knowledge of Kubernetes operations and troubleshooting.

Responsibilities

• Platform operations & infrastructure support (50%).
• Deployment & containerization (25%).
• Collaborate with IT, security, and network teams to resolve tickets and implement changes.
• Deploy and support ML models in production and monitor data pipelines.

Skills

DevOps

Cloud infrastructure

MLOps

AIOps

Python

CI/CD

Docker

Kubernetes

Networking fundamentals

Tools

Terraform

Bicep

ARM templates

Azure DevOps

Kubernetes tooling

Job description

The AI Office is seeking an AI Infrastructure Engineer to own the reliability of the Azure-based AI and analytics platform and to operationalize AI solutions into production. This role sits at the intersection of cloud infrastructure, DevOps, MLOps, and AIOps—keeping production data and model pipelines running while provisioning and deploying the environments new AI use cases depend on. It supports a portfolio spanning commodity forecasting, industrial optimization, credit risk, and turnaround and maintenance AI initiatives.

Effort Allocation

Platform operations & infrastructure support 50%

Deployment & containerization 25%

Required Qualifications

• 5+ years of experience in DevOps, cloud infrastructure, or MLOps roles.
• Registry, Key Vault, Storage, and Entra ID / App Registrations.
• Proficiency in Python and shell scripting.
• Ability to manage cloud services using Infrastructure-as-Code tools.
• Docker containerization and CI/CD pipeline experience (Azure DevOps preferred).
• Working knowledge of Kubernetes operations and troubleshooting.
• Networking fundamentals: private endpoints, firewall rules, DNS, and SSL/TLS.
• Demonstrated experience deploying and supporting machine learning models in production.
• ETL development and data pipeline monitoring.
• Strong written and verbal communication; able to work directly with enterprise IT, security, and network teams to drive tickets to resolution.

Preferred Qualifications

• Azure certifications (AZ-104, AZ-400, or DP-100).
• Experience with Microsoft Fabric or Azure Synapse.
• Experience with Azure AI tools (Foundry, Search, etc.) is a plus.
• Infrastructure-as-code experience (Terraform, Bicep, or ARM templates).
• Experience in an enterprise environment with formal change control and security review processes.
• Exposure to Streamlit, FastAPI, or similar Python application frameworks