Job Title: Director – Healthcare Data and AI Solution Architect

About the Role:

As the Director – Healthcare Data and AI Solution Architect, you are a key technology leader within the Data Office, responsible for defining and championing the data and AI-specific architectural components across PureHealth’s technology ecosystem, in close collaboration with the Technology Office.

This role is pivotal in building the foundation for data-driven innovation at PureHealth. You will design and implement a robust, scalable, and secure architecture tailored to support PureHealth’s data-driven AI initiatives, ensuring deep integration with the overall data strategy and governance framework.

You will translate complex business requirements into clear technical specifications, ensuring compliance with industry standards and best practices, while overseeing the integration of multiple data sources and AI components into a unified system aligned with PureHealth’s data governance and security standards.

Reporting to the Executive Director of AI & Data, you will lead a team of architects and collaborate closely with technical teams across both the Data and Technology Offices to bring the company’s AI vision to life.

Key Responsibilities

1. Architectural Leadership

• Define and maintain a comprehensive and scalable data and AI architecture that supports PureHealth’s AI initiatives, ensuring alignment with the broader enterprise architecture.
• Develop and implement best practices for data storage, processing, integration, security, and governance in compliance with regulatory requirements.
• Provide technical leadership and strategic guidance to engineering teams across both the Data and Technology Offices.
• Evaluate existing systems and processes from a data and AI perspective, identifying areas for optimization.

2. Data and AI Solution Design

• Lead the design and development of secure, scalable data pipelines, data lakes, and AI development platforms.
• Define and implement architecture patterns for data ingestion, transformation, and consumption by AI systems.
• Develop detailed technical specifications, blueprints, and documentation for AI and data infrastructure.
• Establish and maintain standards for data governance, data quality, and access control.
• Ensure architectural designs enable rapid iteration, scalability, and alignment with the strategic data roadmap.

3. Technical Oversight & Collaboration

• Oversee the technical aspects of design, development, and deployment of AI products and platforms.
• Collaborate with cross-functional teams (data science, product, operations, and business) to ensure seamless integration of AI solutions.
• Ensure all solutions are scalable, reliable, secure, and compliant with healthcare industry standards (e.g., HL7 FHIR, HIPAA).
• Develop and manage a continuous evaluation process for emerging technologies, assessing their suitability for long-term roadmap goals.

4. Team Mentorship & Skill Development

• Mentor and guide a team of architects and engineers, fostering technical excellence and professional growth.
• Provide training and coaching on new tools, technologies, and frameworks related to data and AI architecture.
• Cultivate a culture of collaboration, continuous learning, and innovation within the Data and Technology Offices.

Qualifications

Minimum Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or a related field.
• 12+ years of experience in IT architecture, data engineering, or software engineering, including at least 7 years focused on data and AI architecture.
• Proven experience in designing and implementing scalable data platforms, pipelines, and infrastructure using modern cloud technologies (AWS, Azure, or Google Cloud).
• Strong expertise in data modeling, data warehousing, integration, and governance principles.
• Solid understanding of AI frameworks and infrastructure requirements to support data-driven applications.
• Hands-on experience with relational and NoSQL databases, including data security and performance optimization.

Preferred Qualifications

• Master’s or Ph.D. in Computer Science, Data Engineering, or related field.
• Hands-on experience with machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Prior experience working with healthcare or biomedical data.
• Experience operating within matrix organizations and distributed teams.
• Certification in data governance or data management (e.g., CDMP, DAMA).