AI Platform Architect & Platform Ops Lead

MRO; United States; On-site; USD 106,000 - 143,000; Full time

Job summary

MRO is seeking an AI Platform Architect to own the platform layer of our AI tooling, provisioning Claude, Copilot, and other services. This hands-on role builds and maintains the infrastructure, maps costs, and delivers lightweight automations to keep the platform running smoothly.

You will collaborate with security, IT, and end users across the company, enforce governance, implement access control, and monitor usage and ROI across internal AI initiatives, while advancing adoption and efficiency.

Qualifications

• Hands-on experience configuring and deploying AI tools.
• Proactive in AI tooling adoption and internal experiments.
• 3–5 years in cloud/platform/DevOps or AI operations.
• Experience with HIPAA/SOC 2/HITRUST frameworks in AI contexts.

Responsibilities

• Administer and configure AI tools and platforms: provisioning, configuration, usage monitoring.
• Own the platform layer for AI context at scale: registry, access control, and infra.
• Build and ship lightweight internal tooling and automation for the platform.
• Own AI transformation analytics: dashboards for adoption, usage, cost, ROI.
• Monitor AI tool health and support cloud operations for AI workloads.
• Configure security settings and collaborate with InfoSec for tool approvals.
• Maintain AI governance artifacts and respond to security reviews.
• Support vendor due diligence and risk assessments for AI initiatives.

Skills

AI tooling fluency

Cloud/DevOps

Python scripting

SaaS administration

Security/compliance awareness

Documentation writing

Tools

GCP

Azure

AWS

Docker

Kubernetes

Terraform

Job description

MRO is seeking an AI Platform Architect to own the platform layer of our AI tooling, provisioning Claude, Copilot, and other services. This hands-on role builds and maintains the infrastructure, maps costs, and delivers lightweight automations to keep the platform running smoothly.

You will collaborate with security, IT, and end users across the company, enforce governance, implement access control, and monitor usage and ROI across internal AI initiatives, while advancing adoption and efficiency.