AI​/ML Architect

Title: AI Engineer – Architecture & Foundry Deployment

Location: Houston, TX (Onsite Required)

Position Type: Long-term Contract

This team is driving the standardization of architecture across several large-scale, bespoke AI initiatives (“moonshots”) related to commercial optimization, workflows, and exploration. The goal is to create repeatable, scalable architectures that support enterprise-wide AI adoption.

Engineers in this role will receive high-level requirements from senior technical leaders and architects and translate them into practical, production-ready designs and deployments.

This position is posted under the Machine Learning Engineer title due to internal pay banding, but the work aligns more closely with an AI Engineer focused on architecture, deployment, infrastructure automation, and enterprise-scale AI platforms.

This role does not involve building or training models. Instead, the emphasis is on systems design, architecture, deployment, and hands-on work within Microsoft Foundry
.

• 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.

• 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
• Managing token limits across regions and subscriptions
• 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

• Traditional ML or data science exposure
• Experience with Azure Kubernetes Service (AKS)