AI Engineer

Key Responsibilities
Design and deploy standardized, reusable architectures supporting multiple enterprise AI products.
Work hands-on within Microsoft Foundry (previously AI Studio), including agent/sub-agent deployment, grounding configuration, and token management.
Build and maintain Ansible roles to automate infrastructure provisioning, configuration, and deployment of Foundry and Azure resources.
Use Ansible as an abstraction layer to manage complex, large-scale Azure environments across multiple regions and subscriptions.
Support enterprise-wide Foundry deployments, including environment separation (prod/test/experimental) and regional/subscription architectures.
Assist in building automation and integration patterns that streamline AI development and operations.
Collaborate with software engineers, architects, and platform teams to accelerate standardization efforts.
Work with Azure-based AI and ML tooling as needed, including Azure ML and AKS.

Must-Have Qualifications
Strong Software Engineering background, including:
Designing production-grade systems
Applying reusable patterns, abstractions, and architectural standards
Hands-on experience with Microsoft Foundry, including:
Deploying and managing Foundry agents/sub-agents
Configuring grounding
Managing token limits across regions and subscriptions
Multi-region/multi-sub deployment patterns
AI/ML architecture experience, particularly:
Deployment patterns
Environment separation and promotion paths (prod/test/experimental)
Infrastructure-as-Code (IaC) with Ansible, including:
Building Ansible roles
Using Ansible as a configuration management and abstraction layer
Automating Azure resource deployments via Ansible scripts

Nice-to-Have Skills
Azure Machine Learning (pipelines, endpoints, registries)
Traditional ML or data science exposure
Experience with Azure Kubernetes Service (AKS)