Senior Director, AI Platform Architecture

About the Team

CRG Digital AI is the engine that translates our digital strategy into scalable, production-ready AI capabilities that drive measurable business impact. Operating in close partnership with Product, Data, and Engineering, the team embeds AI across our digital portfolio to accelerate clinical trial execution, enhance data-driven decision-making, and unlock differentiated value for our customers. Through a combination of centralized platforms, standards, and federated execution, CRG Digital AI enables rapid innovation while ensuring consistency, quality, and responsible AI practices.

About the Position

Reporting to the VP, Head of Analytics and AI, the Senior Director, AI Platform Architecture is a senior leadership role within CRG Digital responsible for defining, building, and scaling the foundational AI platform that enables the rapid development, deployment, and operation of AI-enabled products and solutions across CRG. This leader owns the end-to-end AI platform strategy, architecture, and delivery model—ensuring that AI capabilities are scalable, reusable, secure, and production-ready. Operating at the intersection of Applied AI (AAI), Data Platforms, and Digital Engineering, this role serves as the backbone of CRG’s AI ecosystem—providing the tools, infrastructure, standards, and services required to accelerate AI innovation while maintaining governance, compliance, and operational excellence. The Director will enable both centralized and federated AI execution, empowering product and engineering teams to build AI solutions efficiently and consistently.

Key Responsibilities

• AI Platform Strategy & Ownership
  • Define and execute the AI platform strategy and roadmap, aligned to CRG Digital and AI priorities
  • Establish the AI platform as a shared capability layer supporting all AI-enabled products and workflows
  • Ensure alignment with enterprise architecture, data platform (MDP), and security strategies
  • Drive a platform-first approach to AI development, enabling reuse and scalability across domains
• Platform Architecture & Engineering
  • Lead the design and development of the AI platform architecture, including:
  • Model development, training, and deployment frameworks
  • MLOps and LLMOps pipelines
  • Model serving, monitoring, and lifecycle management
  • Integration with data platforms (e.g., Snowflake, Databricks)
  • Ensure platform supports GenAI, agentic workflows, and traditional ML use cases
  • Establish standards for performance, scalability, reliability, and cost efficiency
• Reusable AI Capabilities & Tooling
  • Build and scale reusable AI components, including:
  • Model libraries and templates
  • Prompt frameworks and orchestration tools
  • Workflow automation and agent frameworks
  • Enable rapid development through self-service tools and developer enablement
  • Reduce duplication and accelerate time-to-market through standardization and reuse
• MLOps, Governance & Responsible AI Enablement
  • Establish and operationalize AI lifecycle management practices, including:
  • Model versioning, validation, deployment, and monitoring
  • Performance tracking and drift detection
  • Partner with AI Risk/Governance teams to embed compliance, security, and responsible AI principles into the platform
  • Ensure auditability, traceability, and adherence to regulatory