AI Platform Architect

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

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Life Insurance

401(k)

Job summary

MRO Corporation seeks an AI Platform Architect to own the platform layer for enterprise AI tooling, including the registry, access control, and MCP server infrastructure. You will provision Claude, Copilot, and other tools, build automation, and monitor usage and costs across departments.

The role requires hands-on cloud experience (GCP/Azure/AWS), scripting, and strong governance knowledge to enable safe, scalable AI adoption. This is a senior, hands-on platform role in a regulated environment.

Qualifications

• Demonstrated AI-native fluency: daily hands-on use and configuring AI tooling.
• Initiative and resourcefulness with AI; often the go-to for tooling questions.
• 3–5 years in technical roles spanning cloud, platform, DevOps, or AI operations, ideally in regulated industries.
• Hands-on cloud experience across GCP, Azure, or AWS with containers/ services.
• Scripting and automation proficiency (Python or similar) with data analysis and dashboards.
• Experience administering enterprise SaaS platforms (user management, SSO, usage analytics, cost tracking).
• Knowledge of HIPAA Privacy/Security Rules, SOC 2 Type II, or HITRUST and their AI tool implications.
• Strong technical writing for documentation, governance, and security artifacts.

Responsibilities

• Administer and configure AI tools and platforms, provisioning, feature configuration, usage monitoring, and optimization.
• Own the platform layer for AI context at scale: the registry, access control, and infrastructure for prompts, skills, workflows, MCP servers, and connectors.
• Build and ship lightweight internal tooling and automation: deployment scripts, self-service provisioning, usage and cost dashboards, monitoring.
• Own AI transformation analytics and reporting with IT and Engineering: dashboards for adoption, usage, cost per tool, and ROI across initiatives.
• Monitor AI tool health, track token and compute costs, flag anomalies, and support cloud operations for AI workloads.
• Configure and review security settings for MCP servers, connectors, and tools; collaborate with InfoSec for tool security approvals.
• Maintain AI governance assets: AI FAQs, security questionnaire library, responses to security reviews, and compliance content.
• Support vendor due diligence and risk assessments; develop AI governance documentation (risk framework, workflow catalog, PHI handling).

Skills

AI-native fluency

Cloud/DevOps

Scripting (Python)

Enterprise SaaS admin

Security governance

Technical writing

Tools

GCP

Azure

AWS

Kubernetes

Job description

Overview

The AI Platform Architect is a hands-on, AI-native builder and operator who owns the platform layer of MRO's AI tooling - theagentic tools, access control, andtheinfrastructure on which prompt libraries, skills, repeatable workflows, MCP servers, and connectors live.This role will beprovisioning and configuring enterprise AI platforms like Claude, MS Copilot, and GitHub Copilot; supporting LLM API operations and cloud resources; instrumenting adoption, usage, cost, andefficiencyanalytics; and shipping the lightweight automationsthat make the platform run smoothly. This person uses modern AI and agentic tools daily and brings early-adopter resourcefulness torollingthem out for others - fast, pragmatic, and hands-on. This role also partners closely with security, compliance, IT, and users across all departments toclear tools for safe use quickly.

Responsibilities

• Administer and configure AI tools and platforms (Claude, MS Copilot, GitHub Copilot, LLM API operations, and others): provisioning, feature configuration, usage monitoring, and optimization, in partnership with IT admin/infrastructure and ServiceDesk.
• Own the platform layer for AI context at scale: the registry, access control, and infrastructure on which prompt libraries, skills, repeatable workflows, MCP servers, and connectorslive.
• Build and ship lightweight internal tooling and automation in service of the platform: deployment scripts, self-service provisioning, usage and cost dashboards, and monitoring.
• Own AI transformation analytics and reporting in partnership with IT and Engineering: build andmaintaindashboards tracking adoption, usage, cost-per-tool, and ROI across internal and product-embedded AI initiatives.
• Monitor AI tool health, track token and compute costs, flag anomalies, and support cloud operations for AI workloads; partner with Engineering and IT on LLM API operations and cloud resource deployment.
• Configure and review security settings for MCP servers, connectors, and AI tools to enable fast, safe rollouts; partner with InfoSec on AI tool security approval and monitoring across developer and non-developer populations.
• Maintain AI governance and security-acceleration assetsfor the AI domain: AI FAQs and the security questionnaire library; respond to enterprise AI security reviews; contribute AI-specific content to RFP responses, compliance questionnaires, and contracting support for the commercial org as needed.
• Support AI vendor due diligence and third-party risk assessments; develop andmaintainAI governance documentation (risk framework, AI workflow catalog, and PHI handling protocols).

Qualifications

Required Qualifications:

• Demonstrated AI-native fluency: daily hands-on use of modern AI and agentic tools and experience configuring, deploying, or administering these tools for others - not just using them.
• Demonstrated initiative and resourcefulness in AI (self-directed learning, side projects, internal experiments); often the recognized go-to person for AI tooling questions on their current team.
• 3-5 years in technical roles spanning cloud, platform, DevOps, or AI operations, ideally within healthcare or another regulated industry.
• Hands-on cloud experience across GCP, Azure, or AWS: provisioning and configuring resources, and working with containers/services (e.g., Docker, Kubernetes, or equivalent).
• Scripting and automationproficiency(Python or similar), plus strong data analysis, reporting, and dashboard-creation skills.
• Experience administering enterprise SaaS platforms (user management, SSO configuration, usage analytics, cost tracking).
• Working knowledge of HIPAA Privacy/Security Rules, SOC 2 Type II, or HITRUST frameworks, and how they apply to AI tooling.
• Strong technical writing skills for documentation, governance, and security artifacts.

Preferred Qualifications:

• Hands-on DevOps tooling experience: CI/CD and Infrastructure-as-Code (e.g., Terraform).
• Experience with cloud cost management and FinOps practices.
• Experience with AI/ML-specific security considerations (model governance, prompt-injection risks, MCP/connector security, data handling).
• Experience with enterprise AI platforms (Vertex AI, Azure AI Foundry, Bedrock).
• Familiarity with BI/analytics pipelines (BigQuery, SQL, Python).
• Background in healthcare data exchange (FHIR, HL7, clinical data workflows).

Authenticity is essential to our hiring process. Submissions or interview responses created withAI are easily identified and will remove you from consideration. The same applies to using AI tools during interviews-we want to hear directly from you. We may also use technology to detect AI-generated content. Please share your genuine experiences and perspective as it's the only way we can truly get to know you.

Total Compensation Base pay is one element of the total compensation package. Eligible employees may also receive an annual cash bonus and have access to a comprehensive benefits offering, including medical, dental, vision, life insurance, and a 401(k) plan.

Salary Range It is not typical for an individual to be hired at or near the top of the range. Individual pay may be influenced by factors such as skills, qualifications, experience, licensure, certifications, geographic location, and internal equity.

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Pay Range

USD $106,000.00 - USD $143,000.00 /Yr.