Marketing Manager, AI Content Experience Engineer

Macmillan Learning

Major responsibilities include, but are not limited to:

AI Content Strategy & Systems Architecture for Experiential Marketing

• Design and execute comprehensive AI-powered content strategies that support live events, webinars, conferences, website, and immersive brand experiences through systematic content engineering approaches.
• Craft and refine prompts for AI tools (GPT-4, Claude, Descript) to produce desired experiential content outputs ensuring accuracy, relevance, and brand consistency.
• Create and manage AI content automation workflows that transform experiential data and insights into ready-to-publish assets for events and brand activations.
• Architect structured content types, personalization techniques, and interactive experiences powered by AI specifically for experiential marketing applications.
• Establish content governance protocols and quality control measures that ensure AI-generated experiential content meets editorial excellence and brand voice standards.

Technical Content Infrastructure & Optimization

• Define site architecture, internal linking structures, and schema strategies specifically for experiential content optimization and event-related digital properties.
• Implement programmatic SEO practices and Generative Engine Optimization (GEO) to ensure AI-powered search visibility for experiential content and event discovery.
• Collaborate with developers to integrate content systems within CMS platforms for experiential marketing needs and event content management.
• Build and maintain content automation workflows that support real-time content adaptation during live experiences and events.
• Optimize content delivery systems across platforms for personalized user experiences during high-traffic experiential moments.

Content Performance Analysis & Data-Driven Strategy

• Utilize AI-driven analytics tools to gain insights from experiential and content data to extract actionable intelligence for strategy refinement.
• Analyze and interpret complex data sets from experiential touchpoints to drive data-driven content strategies for events and brand experiences.
• Create and manage experiential content and Share of Voice dashboards that measure engagement rates, brand sentiment, experience quality scores, and post-event content performance metrics.
• Conduct systematic analysis of AI-generated content effectiveness using technical measurement approaches.
• Benchmark AI content performance against traditional methods using comprehensive data analysis and interpretation.

AI Tool Management & Content Engineering Innovation

• Evaluate, test, and recommend new AI content creation platforms and technical tools specifically for experiential marketing applications.
• Manage relationships with AI content vendors and stay current on emerging content engineering technologies for live events and brand experiences.
• Develop internal AI content capabilities and establish best practices for prompt engineering, content automation and technical content optimization.
• Create comprehensive documentation and training materials for AI content tools, technical processes, and content engineering workflows.
• Monitor AI tool performance, costs, and ROI through systematic technical analysis specifically for experiential marketing applications.