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.

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
• Build and scale a modern AI-native execution layer that operationalizes AI-driven decisions into real-world actions
• Establish a high-throughput engineering model driven by rapid iteration cycles, automation-first development workflows, 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
• 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
• Partner Strategy & Capability Scaling to define and manage the ecosystem of engineering and platform partners, drive effective onshore/offshore and partner delivery models aligned to group needs, ensure partners contribute to reusable assets and platform capabilities and speed and quality of delivery, and lead internal capability building in AI engineering, platform engineering and automation and orchestration capabilities
• Talent & Organizational Leadership to 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, foster a culture of engineering excellence, innovation and reuse and accountability and continuous improvement

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