Director of AI Changemaker, SharkNinja

• 8+ years in AI/ML, HR transformation, talent operations, or technology-driven change management
• Strong technical fluency in AI/ML: you can evaluate tools, assess platforms, and hold your own with engineers and data scientists
• Deep understanding of enterprise HR operations (talent access, talent experience, HR service delivery, people analytics) and how AI reshapes HR work
• Proven track record leading large-scale transformation in complex, multi-stakeholder environments
• Ability to bridge technical and business: you can tell IT what to build and tell HR leadership what outcome it delivers
• Decisive, action-oriented, and comfortable in ambiguity where speed matters more than perfection

Desirable

• Reports to: VP, Chief of Staff to the CEO
• Dotted Line: EVP, Chief People Officer
• The Director, AI Change Maker is a high-impact, strategic / doer role at the intersection of People and Culture. The successful Director, AI Change Maker, People & Culture will operate as a player/coach, co-leading both the strategy and the hands-on project management execution of AI integration and work reimagination across SharkNinja – from hire to retire, service delivery, and enterprise storytelling – and will be the connective tissue that carries AI forward in our ways of working in all areas of the company
• You will build the data foundation, deploy AI capabilities, and transform workflows so that SharkNinja’s People & Culture organization operates faster, smarter, and delivers greater impact enterprise-wide
• The Director, AI Change Maker carries a dual mandate: drive the current portfolio of AI initiatives to measurable completion, and partner directly with P&C leadership to shape what comes next. You do more than just deliver a fixed list of projects
• You are here to build the AI capability and solutions that transform how People & Culture (P&C) works -- today and in the future. You will be measured on adoption, speed, and measurable business impact. You report directly to the VP, Chief of Staff to the CEO, with a dotted line to both the Chief People Officer
• Co-own the AI transformation roadmap across the full P&C function, identifying overlaps, dependencies, and consolidation opportunities
• Deploy work-reimagination and skills-mapping platforms to enable smarter workforce deployment across P&C and the enterprise
• Build and scale AI coaching tool for managers, enabling always-on development support, real-time feedback, and career pathing at a fraction of the cost of external coaching tools
• Build enterprise AI capability programs, run cross-functional sprints, and embed new ways of working at scale -- serving as the connective tissue between P&C and every other function's AI transformation
• Sequence and prioritize ruthlessly: act as PMO to drive each initiative to completion before starting the next, unless directed otherwise
• Leverage employee-first HR technology (e.g. Oracle, Greenhouse, Lattice)
• Work with enterprise storytelling and communications teams to build AI-augmented content production models, shifting from fully human time-consuming workflows to a majority-AI speed and high quality production model
• Build agents and AI-powered workflows that turn company moments into internal stories in near real time -- newsletters, town hall recaps, and internal posts drafted and published in hours, not days
• Deploy AI agents, automations, and workflows that augment service-level tasks across P&C -- scheduling, sourcing, onboarding, content production, information gathering and sharing
• Accelerate candidate sourcing and scheduling through AI agents, compressing time-to-fill and widening the funnel while reducing coordinator dependency
• Shift P&C to a customer-centric service delivery model with easily accessible key information (e.g. benefits, retirement, policy, personal info, manager tools, etc.)
• Drive hands-on AI adoption into the P&C organization
• Change work for the future, not just execute on change management
• Drive change management across large, global workforces with varying levels of AI fluency
• Translate complex AI capabilities into practical, adoptable solutions
• Establish success metrics, track adoption, and report measurable outcomes to executive leadership
• Champion a culture of experimentation: fast iteration, learning from failure, and scaling what works