Director of AI

PlanHub

11d•Remote

About The Position

Define, execute, and own the organization’s AI vision, strategy, and long-term roadmap, ensuring alignment with business objectives and measurable outcomes Lead, build, and scale high-performing AI, ML, and data science organizations, establishing clear operating models, best practices, and governance Oversee the design and adoption of agentic AI and generative AI systems, including content understanding, information retrieval, content generation, and multi-agent workflows. This spans from ingestion and content management, model selection, indexing patterns, orchestration frameworks, evaluation frameworks, and ongoing monitoring, operations, and improvement. Own the strategic direction for ML-based recommendation and personalization systems, guiding initiatives across content discovery, ranking, personalization, and user engagement Lead the business and product with Data Science to understand network health and build data-driven systems to optimize liquidity, improve retention, and enter new markets Establish success metrics, experimentation frameworks (e.g., A/B testing), and continuous improvement processes for AI-driven products Oversee the organization’s AWS-based AI and ML platform, including governance of SageMaker, Bedrock, ML platforms, and deployment infrastructure Set standards for AI/MLOps, model lifecycle management, monitoring, cost optimization, and scalability, in partnership with Engineering and Platform teams Ensure AI solutions meet requirements for security, privacy, ethics, and regulatory compliance, driving responsible AI practices Act as the AI advisor to senior leadership, influencing product strategy, investment decisions, and external partnerships

Requirements

10+ years of industry experience in AI / machine learning, with significant leadership responsibility
Proven leadership of customer-facing recommendation systems, information retrieval, and personalization platforms
Demonstrated experiencing leading the design, build, and operations of generative/agentic-AI products, including a strong understanding of LLMs, RAG, and agentic AI concepts
High agency and a sense of urgency to create value for customers in an iterative, test-and-learn product development cycle
Experience overseeing AI systems deployed on AWS
Track record of leading cross-functional AI initiatives
Ability to communicate complex AI topics to executive and non-technical audiences
Experience aligning AI investments with measurable business outcomes
Experience leading AI strategy at scale
Familiarity with AI governance frameworks and regulatory landscapes

Responsibilities

Define, execute, and own the organization’s AI vision, strategy, and long-term roadmap
Lead, build, and scale high-performing AI, ML, and data science organizations
Oversee the design and adoption of agentic AI and generative AI systems
Own the strategic direction for ML-based recommendation and personalization systems
Lead the business and product with Data Science to understand network health
Establish success metrics, experimentation frameworks (e.g., A/B testing)
Oversee the organization’s AWS-based AI and ML platform
Set standards for AI/MLOps, model lifecycle management, monitoring, cost optimization, and scalability
Ensure AI solutions meet requirements for security, privacy, ethics, and regulatory compliance
Act as the AI advisor to senior leadership