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Cloud and AI Platform Architect - Remote

Healthesystems
CompanyHealthesystems
CategoryData & Analytics
LocationRemote-Work From Home
RemoteRemote
EmploymentNot stated
LevelLead
SalaryNot stated by the employer
Posted22 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
Healthesystems offers workplace flexibility with our Work-From-Home model, and a competitive compensation and benefits package including healthcare coverage, PTO, paid holidays, 401(k), company-provided life insurance/disability coverage, wellness options, and more. Healthesystems welcomes candidates from these states: AL, AZ, CO, FL, GA, ID, IN, LA, MD, MS, MO, NC, OH, OK, PA, SC, TN, TX, UT, VA Summary: This position provides enterprise-level technical and architectural leadership across cloud platform architecture, infrastructure modernization, and the organization’s emerging AI platform and ecosystem. The role is responsible for guiding cloud transformation, infrastructure optimization, resiliency and disaster recovery design, and AI enablement. As a primary architecture partner for IT Services, Engineering, Information Management, Security, and business stakeholders, this position establishes standards, reference architectures, integration environments, governance guardrails, and reusable platform capabilities that support strategic business outcomes, operational stability, cost optimization, and responsible AI adoption. Key Responsibilities: “To simplify complexities for each customer.” Lead culture of change for cloud adoption Influence culture / change in behaviors toward the adoption and consumption of cloud services Inspire a culture that resist the urge to execute "Business as usual" Lead organization to adopt / incorporate cloud computing correctly and in the most effective manner Develop and coordinate the cloud architecture Coordinate cloud architecture across all applicable areas. Areas will include but not be limited to AppDev, IM, Governance, Infrastructure, EA, Security, .etc Refine and coordinate the adoption of the Cloud Strategy Work with stakeholders to identify and clearly articulate when to leverage cloud services and when to no. Develop process by which IT & the Business can easily select the appropriate cloud resource per application Create a process or criteria for the evaluation and selection of cloud providers and services.  Work closely with stakeholders to identify risk posed by cloud computing and develop risk mitigation strategy for overcoming risks. Work stakeholders to ensure the most cost-effective cloud services are procured Collaborate with stakeholders to move from traditional infrastructure vendors toward cloud providers. Partner with EA and other stakeholders to create governance for on-prem and cloud infrastructure Collaborate with architecture, SMEs, and stakeholders to evaluate, design, and validate cloud and infrastructure architectures. Represent infrastructure and cloud reference architectures within the broader enterpise’s architecture community Work with architects and SMEs to create designs that map technical components to infrastructure that satisfies functional and non-functional requirements Define and guide the enterprise AI platform and ecosystem architecture, including AI infrastructure guidance, agent gateway capabilities, model integration patterns, deployment patterns, and reusable shared services that enable secure and scalable AI adoption. Establish architecture standards and governance guardrails for responsible AI adoption, incorporating guidance form the organization’s AI Governance group to drive AI observability, lifecycle management, and controls to prevent fragmented or duplicative AI solutions and platforms. Drive sustainable cloud and infrastructure cost optimization by identifying right-sizing opportunities, improving spend visibility, defining cloud financial management practices, and balancing cost savings with reliability, security, and performance requirements. Serve as a system-thinking architecture leader who connects cloud, infrastructure, integration, data, security, and AI decisions across initiatives to ensure cohesive execution, reduced rework, and align
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