AI Platform Architect

🕒 il y a 1 mois

🇺🇸 États-Unis – Télétravail

💵 $106 000 - $143 000 / an

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🔙 Ingénieur Back-end

🗣️🇺🇸🇬🇧 Anglais requis

D'où vient cette offre

Publiée sur la page carrières de MRO, pas via un site d'emploi

Repérée par Remote Rocketship il y a 1 mois

Toujours ouverte sur le site de MRO. Vérifiée il y a 11 minutes.

Logo of MRO

MRO

1001 - 5000 employés

🏥 Santé

☁️ SaaS

📋 Conformité

💰 Series unknown en 2019-11

Healthcare • SaaS • Compliance

MRO est une entreprise de logiciels de santé qui offre une plateforme d'échange de données cliniques (CDXP) et des solutions modulaires pour organiser, normaliser et échanger en toute sécurité des données cliniques entre les fournisseurs de soins, les assureurs, les registres et les demandeurs de données cliniques. MRO aide les hôpitaux, les systèmes de santé, les pratiques ambulatoires et les assureurs à rationaliser les flux de travail de divulgation d'informations, de conformité, de reporting de qualité/MIPS, de suivi des ACO, et d'intelligence clinique en se connectant à des centaines de dossiers de santé électroniques disparates, réduisant ainsi la charge administrative et accélérant la délivrance de soins centrés sur le patient. L'entreprise met l'accent sur la sécurité et la conformité réglementaire et a été reconnue par les prix « Best in KLAS » pour la divulgation d'informations.

Description

• Administer and configure AI tools and platforms including Claude, MS Copilot, GitHub Copilot, and LLM APIs • Provision tools, configure features, monitor usage, and optimize platforms in partnership with IT administration, infrastructure, and ServiceDesk • Own the registry, access control, and infrastructure supporting prompt libraries, skills, repeatable workflows, MCP servers, and connectors • Build and ship lightweight internal tooling and automation, including deployment scripts, self-service provisioning, usage and cost dashboards, and monitoring • Build and maintain dashboards tracking adoption, usage, cost-per-tool, and ROI across internal and product-embedded AI initiatives • Monitor AI tool health, token and compute costs, anomalies, and 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 • Partner with InfoSec on AI tool security approval and monitoring • Maintain AI FAQs and security questionnaire libraries • Respond to enterprise AI security reviews and contribute AI-specific content to RFP responses, compliance questionnaires, and contracting support • Support AI vendor due diligence and third-party risk assessments • Develop and maintain AI governance documentation, including risk frameworks, AI workflow catalogs, and PHI handling protocols

🎯 Exigences

• Daily hands-on use of modern AI and agentic tools • Experience configuring, deploying, or administering AI tools for others • Initiative and resourcefulness in AI, including self-directed learning, side projects, or internal experiments • 3–5 years in technical roles spanning cloud, platform, DevOps, or AI operations • Experience ideally within healthcare or another regulated industry • Hands-on cloud experience across GCP, Azure, or AWS • Experience provisioning and configuring cloud resources • Experience working with containers/services such as Docker, Kubernetes, or equivalent • Scripting and automation proficiency in Python or similar • Strong data analysis, reporting, and dashboard-creation skills • Experience administering enterprise SaaS platforms, including user management, SSO configuration, usage analytics, and cost tracking • Working knowledge of HIPAA Privacy/Security Rules, SOC 2 Type II, or HITRUST frameworks and their application to AI tooling • Strong technical writing skills for documentation, governance, and security artifacts • Preferred: hands-on DevOps tooling experience with CI/CD and Infrastructure-as-Code, such as Terraform • Preferred: cloud cost management and FinOps practices • Preferred: AI/ML-specific security considerations, including model governance, prompt-injection risks, MCP/connector security, and data handling • Preferred: enterprise AI platforms such as Vertex AI, Azure AI Foundry, or Bedrock • Preferred: familiarity with BI/analytics pipelines including BigQuery, SQL, and Python • Preferred: background in healthcare data exchange, including FHIR, HL7, and clinical data workflows

🏖️ Avantages

• Annual cash bonus • Medical insurance • Dental insurance • Vision insurance • Life insurance • 401(k) plan • Comprehensive benefits offering

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