Sr. Director - Solution Architecture (Data and AI)

By bringing an AI-aware approach to modernizing processes and design, this individual will elevate operational intelligence while maintaining rigorous standards for safety and compliance. They will partner with senior business & operations leadership to define architectural guardrails, promote consistency, and mentor our engineering and data teams.

Primary Responsibilities:

• Shape the end-to-end architecture across platform, services, and data domains and ensure alignment between technology architecture and operational needs.
• Establish clear patterns, guardrails, and reusable services that support modernization, interoperability and long term sustainability 
• Apply an AI aware mindset to inform design choices, improve clarity of trade-offs, and guide teams toward a shared architecture vision
• Interact with business stakeholders and operations teams to identify automation use cases through AI
• Hands-on experience developing pilots, POCs and incubating new ideas
• Oversee design through the full lifecycle, ensuring reliability, performance, security and cost effectiveness are built in from the start 
• Responsible for the end to end architecture of next generation Privia Data Foundry
• Mentor engineering teams in the use of AI, especially for development, testing, solution documentation and dependency analysis 
• Design solutions informed by healthcare data flows, RCM, clinical workflows, provider and payer contracts, and regulatory expectations 
• Understand how EMR and clinical systems interact with payer platforms to guide integration, data movement 
• Familiarity with value based care and fee for service delivery models 
• Ability to build big data warehouse using Snowflake and other technologies 
• Apply interoperability standards (HL7, X12 FHIR) to ensure systems communicate reliabily and securely 
• Modernize legacy data and technology platforms 
• Lead design reviews and share best practices, and foster a culture focused on simplification, reuse and responsible innovation 
• Encourage sage and effective adoption of AI augmented engineering techniques across teams 
• Identify architectural improvements that reduce operational effort and increase developer productivity 
• Support continuous improvement with metrics, insights and evolving standards - using AI supported analysis where help