This senior-level role involves co-designing AI solutions with the AI Architect and owning the end-to-end implementation, including data pipelines, model training, evaluation, deployment, and MLOps establishment for product delivery. Responsibilities also include owning the reliability, security, and cost of AI services while ensuring HIPAA compliance and collaborating across product, domain, and compliance teams.

The AI Architect is responsible for owning the enterprise AI architecture, standards, and governance for healthcare-grade solutions, establishing reference patterns and guardrails for product teams developing LLM applications and ML services. This role involves defining enterprise architecture standards, owning platform and tooling selection within Azure AI, and embedding security, compliance, and Responsible AI practices into the development lifecycle.

This role leads enterprise-wide readiness, adoption, and workforce capability building for AI, serving as a subject matter expert in AI training and organizational readiness. Responsibilities include designing scalable enablement programs, developing adoption frameworks, and guiding cultural transformation to embed AI into daily operations.

The role involves shaping and executing the technical direction for AI infrastructure and products, focusing on building foundational AI tooling that powers developer productivity across the software development lifecycle. Responsibilities include driving the AI for Developers strategy, making architectural decisions, and championing engineering excellence through high-quality code and reliable systems.