Komen Graduate Training Program UT MDACC
Enterprise AI Architect
Komen Graduate Training Program UT MDACC, Houston, Texas, United States, 77246
Overview
Join the world's premier cancer center as the visionary Enterprise AI Architect, where you will strategically lead the design and implementation of comprehensive AI/ML architectures across the organization. Your expertise will ensure scalable, secure, and compliant AI capabilities that empower transformative innovations in clinical care, operations, research, and education. In this pivotal role, you will shape our institutional AI strategy, establish a robust AI lifecycle management framework, and lead the development of an integrated AI ecosystem combining advanced models, data infrastructure, and commercial platforms. Leveraging hybrid cloud and on-premise infrastructures, you\u2019ll embed rigorous AI governance and operations to guarantee trustworthy, auditable, and impactful AI solutions at scale, driving measurable outcomes across the enterprise. Key Responsibilities
Architect and govern scalable, secure AI/ML platforms aligned with institutional strategy. Collaborate with other institutional architects to ensure alignment across the digital operations ecosystems. Lead multidisciplinary teams to implement AI/ML infrastructure supporting development, deployment, monitoring, and auditability. Integrate AI/ML platforms with HealthIT (Epic, PACS, LIS) and enterprise applications using FHIR, HL7, and DICOM standards. Collaborate with cybersecurity and compliance teams to enforce zero-trust security, IAM, encryption, and HIPAA compliance. Optimize hybrid cloud/on-premises infrastructure leveraging Azure services. Provide strategic guidance on vendor partnerships, platform selection, and integration decisions. Support the implementation of AI lifecycle management, with emphasis on model monitoring, audit trails, and safety/impact tracking to ensure positive clinical, operational, and financial outcomes. Technical Expertise
Deep understanding of AI lifecycle management and AI/ML platform architecture. Knowledge of EPIC, PACS, LIS, and other HealthIT/business systems including ServiceNow, Salesforce, etc. Strong understanding of enterprise architecture frameworks (e.g., TOGAF). Expertise in AI/ML platform infrastructure, including Kubernetes, NVIDIA DGX, and Azure. Experience integrating AI/ML platforms, solutions, models with healthcare IT and business systems. Familiarity with healthcare interoperability and compliance standards: HL7, FHIR, DICOM, HIPAA, FDA guidelines. Extensive hands-on experience with Azure cloud services including Azure ML, AKS, Azure DevOps, and Azure Data Factory. Proficiency in DevOps, CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes). Skilled in network and security architecture, including zero-trust models, IAM, encryption, and secure data transit. Experience implementing AI model monitoring, audit trails, and impact measurement frameworks. Knowledge of enterprise data platforms and data governance frameworks to support AI/ML. Analytical Skills
Translating clinical, operational, and strategic business requirements into robust AI architectures. Experience in risk assessment related to security, compliance, and ethical AI deployment. Quantitative evaluations for AI infrastructure planning and vendor selections. Familiarity with ISO/IEC standards relevant to AI (e.g., ISO/IEC 42001, ISO/IEC 23894), IHE profiles, and other external standards needed for safe and compliant AI/ML deployment in healthcare. Professionalism: Oral and Written
Ability to foster collaborative decision-making with clinical, technical, and executive teams. Strong communication of complex AI strategies and architectures to stakeholders. Capability to craft detailed yet accessible documentation for governance, compliance, and clarity. Ability to prepare strategic reports highlighting impacts, risks, and recommendations for executive stakeholders. Education and Experience
Required Education: Bachelor’s degree. Preferred Education: Master\u2019s degree. Preferred Certifications: TOGAF 9 Certified; Microsoft Certified: Azure Solutions Architect Expert, Epic Cogito/Caboodle/Cognitive Computing Certifications, Certified Kubernetes Administrator (CKA), or equivalent. Required Experience: Ten years of experience in platform technology, including five years in software integration and five years of supervisory/managerial experience. May substitute education with equivalent experience; LEADing Self Accelerate may substitute for one year of management experience. Preferred Experience/Skills: Experience architecting complex hybrid cloud/on-prem infrastructures, AI/ML development and deployment ecosystems, Health IT integration, and governance frameworks; ability to collaborate with senior leadership, clinicians, and technical teams to translate requirements into scalable architectures. Work Location
Remote within Texas only. Equal Opportunity
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by policy or law. Additional Information
Requisition ID: 175349 Employment Status: Full-Time Employee Status: Regular Work Week: Days Minimum Salary: USD 160,500 Midpoint Salary: USD 203,000 Maximum Salary: USD 245,500 FLSA: exempt Fund Type: Hard Pivotal Position: Yes Referral Bonus Available?: Yes Relocation Assistance Available?: Yes
#J-18808-Ljbffr
Join the world's premier cancer center as the visionary Enterprise AI Architect, where you will strategically lead the design and implementation of comprehensive AI/ML architectures across the organization. Your expertise will ensure scalable, secure, and compliant AI capabilities that empower transformative innovations in clinical care, operations, research, and education. In this pivotal role, you will shape our institutional AI strategy, establish a robust AI lifecycle management framework, and lead the development of an integrated AI ecosystem combining advanced models, data infrastructure, and commercial platforms. Leveraging hybrid cloud and on-premise infrastructures, you\u2019ll embed rigorous AI governance and operations to guarantee trustworthy, auditable, and impactful AI solutions at scale, driving measurable outcomes across the enterprise. Key Responsibilities
Architect and govern scalable, secure AI/ML platforms aligned with institutional strategy. Collaborate with other institutional architects to ensure alignment across the digital operations ecosystems. Lead multidisciplinary teams to implement AI/ML infrastructure supporting development, deployment, monitoring, and auditability. Integrate AI/ML platforms with HealthIT (Epic, PACS, LIS) and enterprise applications using FHIR, HL7, and DICOM standards. Collaborate with cybersecurity and compliance teams to enforce zero-trust security, IAM, encryption, and HIPAA compliance. Optimize hybrid cloud/on-premises infrastructure leveraging Azure services. Provide strategic guidance on vendor partnerships, platform selection, and integration decisions. Support the implementation of AI lifecycle management, with emphasis on model monitoring, audit trails, and safety/impact tracking to ensure positive clinical, operational, and financial outcomes. Technical Expertise
Deep understanding of AI lifecycle management and AI/ML platform architecture. Knowledge of EPIC, PACS, LIS, and other HealthIT/business systems including ServiceNow, Salesforce, etc. Strong understanding of enterprise architecture frameworks (e.g., TOGAF). Expertise in AI/ML platform infrastructure, including Kubernetes, NVIDIA DGX, and Azure. Experience integrating AI/ML platforms, solutions, models with healthcare IT and business systems. Familiarity with healthcare interoperability and compliance standards: HL7, FHIR, DICOM, HIPAA, FDA guidelines. Extensive hands-on experience with Azure cloud services including Azure ML, AKS, Azure DevOps, and Azure Data Factory. Proficiency in DevOps, CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes). Skilled in network and security architecture, including zero-trust models, IAM, encryption, and secure data transit. Experience implementing AI model monitoring, audit trails, and impact measurement frameworks. Knowledge of enterprise data platforms and data governance frameworks to support AI/ML. Analytical Skills
Translating clinical, operational, and strategic business requirements into robust AI architectures. Experience in risk assessment related to security, compliance, and ethical AI deployment. Quantitative evaluations for AI infrastructure planning and vendor selections. Familiarity with ISO/IEC standards relevant to AI (e.g., ISO/IEC 42001, ISO/IEC 23894), IHE profiles, and other external standards needed for safe and compliant AI/ML deployment in healthcare. Professionalism: Oral and Written
Ability to foster collaborative decision-making with clinical, technical, and executive teams. Strong communication of complex AI strategies and architectures to stakeholders. Capability to craft detailed yet accessible documentation for governance, compliance, and clarity. Ability to prepare strategic reports highlighting impacts, risks, and recommendations for executive stakeholders. Education and Experience
Required Education: Bachelor’s degree. Preferred Education: Master\u2019s degree. Preferred Certifications: TOGAF 9 Certified; Microsoft Certified: Azure Solutions Architect Expert, Epic Cogito/Caboodle/Cognitive Computing Certifications, Certified Kubernetes Administrator (CKA), or equivalent. Required Experience: Ten years of experience in platform technology, including five years in software integration and five years of supervisory/managerial experience. May substitute education with equivalent experience; LEADing Self Accelerate may substitute for one year of management experience. Preferred Experience/Skills: Experience architecting complex hybrid cloud/on-prem infrastructures, AI/ML development and deployment ecosystems, Health IT integration, and governance frameworks; ability to collaborate with senior leadership, clinicians, and technical teams to translate requirements into scalable architectures. Work Location
Remote within Texas only. Equal Opportunity
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by policy or law. Additional Information
Requisition ID: 175349 Employment Status: Full-Time Employee Status: Regular Work Week: Days Minimum Salary: USD 160,500 Midpoint Salary: USD 203,000 Maximum Salary: USD 245,500 FLSA: exempt Fund Type: Hard Pivotal Position: Yes Referral Bonus Available?: Yes Relocation Assistance Available?: Yes
#J-18808-Ljbffr