Senior Enterprise AI Architect — Healthcare (Remote)

Rush University Medical Center; Chicago (IL); Hybrid; USD 90,000 - 136,000; Full time

Job summary

Rush University Medical Center is seeking an Enterprise AI Architect to design, govern, and enable scalable AI, ML, and analytics architectures across the healthcare enterprise. You will define technical standards, integration patterns, and guardrails to align with clinical workflows, data strategy, cybersecurity, and regulatory requirements.

This senior role bridges data engineering, AI/ML, infrastructure, applications, and cybersecurity, reporting to the Director of AI & Innovation.

Qualifications

• Bachelor’s degree or equivalent experience required.
• 8+ years in IT, data, or solution architecture roles.
• 3+ years designing or supporting AI/ML platforms.
• Hands-on experience designing enterprise-scale data and AI architectures.
• Experience in complex, regulated environments such as healthcare.
• Strong relationship-building and collaborative mindset.

Responsibilities

• Define end-to-end architectures for AI solutions.
• Establish enterprise AI reference architectures, design patterns, and standards.
• Ensure alignment with enterprise IT, cloud, data, integration, and application strategies.
• Evaluate emerging AI technologies, platforms, and tools for healthcare applicability.
• Embed security, privacy, compliance and governance in AI architectures.
• Partner with data scientists and engineers to translate business and clinical use cases into designs.

Skills

Architecture leadership

Cross-functional collaboration

Stakeholder management

Regulated environments

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent experience

Tools

Python

SQL

Cloud platforms

MLOps tooling

Job description

Rush University Medical Center is seeking an Enterprise AI Architect to design, govern, and enable scalable AI, ML, and analytics architectures across the healthcare enterprise. You will define technical standards, integration patterns, and guardrails to align with clinical workflows, data strategy, cybersecurity, and regulatory requirements.

This senior role bridges data engineering, AI/ML, infrastructure, applications, and cybersecurity, reporting to the Director of AI & Innovation.