Executive Director, Applied AI

Work Schedule Standard (Mon-Fri) Environmental Conditions Office 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. This position is a band 10 role, remotely based in the US Position Overview: Reporting into the VP, Head of Analytics and AI, the Executive Director, Applied AI is a senior leadership role responsible for building, operating, and scaling CRG Digital's end-to-end AI engineering and platform capability, anchored in reusable architecture and scalable execution systems. This includes ownership of AI engineering delivery, platform architecture, and the integrated automation layer—ensuring that AI-enabled solutions are production-ready, scalable, and seamlessly embedded into business operations. Operating at the intersection of Applied AI (AAI), Data, and Product Engineering, this leader unifies solution delivery and platform enablement into a cohesive, high-performing system. The role is accountable for both what gets built and how it runs, combining product-aligned engineering teams with a robust, reusable platform that accelerates development, enforces standards, and enables federated AI adoption across CRG. A core part of this mandate is defining and scaling reusable AI architecture patterns, services, and components that support rapid development of AI-enabled capabilities across domains. A strong focus of this role is the development of a modern AI-native execution layer, where AI-driven decisioning, services, and workflows are operationalized through APIs, orchestration frameworks, and automation capabilities. Traditional RPA is evolved and integrated into this broader architecture as one of several execution mechanisms, rather than a standalone capability, ensuring consistency, scalability, and alignment with AI-first design principles. This role plays a crucial part in shaping the next generation of role-based, AI-enabled operations, where AI capabilities are embedded directly into how work is performed. The platform and engineering organization will define the architectural foundation for these operating models, enabling reusable patterns for human–AI interaction, decision support, and autonomous or semi-autonomous execution. The Executive Director, Applied AI partners closely with: • Solution Architecture to translate AI use cases into scalable technical solutions • AI Value Realization & Enablement (AVRE) to ensure solutions are designed for real-world workflow integration • AI Risk & Compliance to embed governance and responsible AI practices into platform and engineering systems • Data and Product teams to align on priorities, architecture, and delivery outcomes This role is critical to enabling CRG's AI strategy by delivering a high-throughput, platform-enabled engineering organization that balances speed, quality, cost efficiency, and regulatory compliance—while laying the architectural and engineering foundation for next-generation AI, agentic systems, and role-based operating models. Key Responsibilities AI Engineering Delivery & Product Integration • Lead product-aligned engineering teams to deliver AI-enabled applications and services at scale, with a strong emphasis on AI-native development practices • Redefine engineering productivity by driving adoption of AI-assisted and agent-based development, including AI coding assistants (e.g., Codex-style tools), agent-enabled code generation, testing, and refactoring and automated documentation and code review workflows. • Establish a target operating model where individual engineers are significantly amplified by AI tooling, enabling 1 engineer to deliver the output of multiple traditional engineers through effective human–AI collaboration. • Shift engineering focus from manual coding to solution architecture and system design, validation, testing, and quality assurance of AI-generated code and integration of AI services into scalable systems. • Own the reliable, high-quality delivery of AI/ML and GenAI solutions, AI-enabled product features and APIs, integrated data and feature pipelines. • Establish a high-throughput engineering model driven by rapid iteration cycles, automation-first development workflows and reuse of components and services. • Partner with Solution Architecture to translate use cases into scalable, production-ready solutions, ensuring alignment between design intent and engineering execution. • Ensure seamless integration of AI capabilities