Senior Director, AI Delivery & Operations

About the role

Reporting to the VP, Head of Analytics and AI, the Senior Director, AI Delivery & Operations 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.

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.

Key Responsibilities

• 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
• Own the reliable, high-quality delivery of AI/ML and GenAI solutions, AI-enabled product features and APIs and integrated data and feature pipelines
• Partner with Solution Architecture to translate use cases into scalable, production-ready solutions, ensuring alignment between design intent and engineering execution
• Integrate and evolve capabilities including APIs and system integrations, workflow orchestration frameworks, intelligent automation (including RPA as a supporting capability)
• Enable execution patterns that support human-in-the-loop, semi-autonomous, and agentic workflows
• Establish and scale end-to-end AI lifecycle management, including model development, validation, deployment and monitoring and versioning, performance tracking, and drift detection
• Embed governance-by-design in partnership with AI Risk & Compliance, including auditability and traceability and secure and compliant development practices
• Define and manage the ecosystem of engineering and platform partners, ensuring partners contribute to reusable assets and platform capabilities and speed and quality of delivery
• Build and lead a high-performing organization across AI engineering, platform engineering and automation and orchestration capabilities
• Define roles, skill models, and career paths aligned to future-state AI capabilities

Qualifications

• Bachelor’s degree required; advanced degree preferred (computer science, engineering, AI/ML, or related field)
• 12 years of experience in software engineering, platform engineering, or technology leadership roles, with a proven track record of building and scaling high-performing engineering organizations
• Demonstrated experience defining and implementing scalable, reusable platform architectures and shared capability layers in complex enterprise environments
• Experience delivering AI/ML and/or GenAI-enabled systems in production, including understanding of model lifecycle, integration patterns, and operational considerations
• Proven ability to evolve engineering organizations toward modern, automation-first and AI-assisted development practices, driving meaningful improvements in speed, quality, and efficiency
• Strong systems thinking with the ability to design scalable, reusable architecture patterns rather than point solutions
• Deep technical and strategic understanding of AI engineering, platform architecture, and modern software systems, with the ability to translate these into business and operational impact
• Ability to operate effectively at both deep technical and executive levels, bridging architecture, engineering execution, and business priorities
• Strong orientation toward automation, reuse, and platform leverage over bespoke development approaches
• Demonstrated ability to lead transformation of engineering practices, including adoption of AI-assisted and agent-enabled development models
• Excellent stakeholder management and communication skills, with the ability to influence across Product, Data, AI, Risk, and Business functions
• Comfortable operating in ambiguity and leading teams through rapidly evolving technology landscapes, including emerging AI and agentic capabilities