AI Infrastructure Engineer

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, Dev Ops, 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.

Platform operations & infrastructure support 50%

Deployment & containerization 25%

• 5+ years of experience in Dev Ops, cloud infrastructure, or MLOps roles.
• Registry, Key Vault, Storage, and Entra  / 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 Dev Ops 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.

• 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