Senior Director, AI Platform Architecture

About the role

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.

Responsibilities

• 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
• 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)
• Establish standards for performance, scalability, reliability, and cost efficiency
• 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
• 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 and enterprise standards
• Federated AI
• Provide self-service platform capabilities to AI Engineering
• Ensure adoption through ease-of-use and standardization
• Provide tooling, frameworks, and guardrails to ensure consistency and quality across distributed teams
• Act as a central enablement layer supporting both AAI and product-aligned engineering teams
• Cross-Functional Integration
• Partner closely with:
• AI Applied (AAI) for solution design and AI architecture
• Data Platforms for data ingestion, quality, and readiness
• Digital Engineering for product integration and delivery
• Define and manage relationships with technology vendors and platform partners (e.g., cloud, AI tooling providers)
• Evaluate and integrate emerging AI technologies and tools into the platform ecosystem
• Optimize the balance between build vs. buy vs. partner decisions
• Team Leadership & Capability Building
• Lead a high-performing team of AI platform engineers, MLOps specialists, and platform architects
• Define skills, roles, and career paths for AI platform talent
• Drive capability building in AI engineering, platform operations, and emerging AI technologies
• Foster a culture of innovation, reliability, and continuous improvement
• Measures of Success
• Adoption and utilization of the AI platform across CRG Digital teams
• Reduction in time-to-deploy AI solutions and increased development velocity
• Increase reuse of AI components and platform capabilities
• Strong performance of AI systems (reliability, scalability, cost efficiency)
• Effective implementation of AI governance and lifecycle management practices
• Development of a scalable and high-performing AI platform organization

Qualifications

• Bachelor’s degree required; advanced degree preferred (computer science, engineering, AI/ML, or related field)
• 12 years of experience in software engineering, data platforms, AI/ML engineering, or platform leadership roles
• Proven track record of building and scaling AI/ML platforms or data platforms in enterprise environments
• Strong understanding of AI/ML and GenAI technologies, MLOps/LLMOps practices and Cloud platforms and modern data architectures
• Experience operating in complex, matrixed organizations with cross-functional stakeholders
• Experience in regulated environments (healthcare/life sciences) preferred