AI Operations & Security, Senior Analyst

This role owns the operational and security backbone of MRO’s AI tooling — the cloud and DevOps foundation that lets AI tools and platforms roll out quickly, securely, and cost-effectively across the organization. The center of gravity is hands-on: provisioning and configuring AI tools and platforms like Claude and MS Copilot, managing AI cloud resources, monitoring tool health and cost, and building the analytics that track adoption and ROI. 

On the security side, the emphasis is on enabling safe rollouts — configuring and reviewing security settings for the emerging agentic context layer of MCP servers, connectors, and AI tools, and partnering with InfoSec to clear these all for use. Also accelerating deal velocity by answering client-facing compliance questionnaires with AI-specific content when needed.   

• Administer and configure AI tools and platforms (Claude, MS Copilot, GitHub Copilot, and others): feature configuration, usage monitoring, and optimization, in partnership with IT admin/infrastructure and ServiceDesk. 
• Configure and review security settings for MCP servers, connectors, and AI tools to enable fast, safe tool rollouts; partner with InfoSec on AI tool security approval and monitoring across developer and non-developer populations. 
• 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 connectors live.   
• Monitor AI tool health, track token and compute costs, flag anomalies, and support cloud operations for AI workloads. 
• Own AI transformation analytics and reporting in partnership with IT and Engineering: build and maintain dashboards tracking adoption, usage, cost-per-tool, and ROI across internal and product-embedded AI initiatives. 
• Partner with Engineering and IT to support LLM API operations and cloud resource deployment. 
• Own AI governance and security acceleration: maintain 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. 
• Manage AI vendor due diligence and third-party risk assessments. 
• Develop and maintain AI governance documentation: risk framework, AI workflow catalog, and PHI handling protocols. 

Required: 

• 3–5 years in cloud operations, DevOps, or IT operations roles, ideally within healthcare or a HIPAA-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). 
• Familiarity with AI tools and agentic workflows. 
• Proficient with data analysis, reporting, and dashboard creation. 
• 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 and security artifacts.

Preferred: 

• 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). 

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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