AI Product Enablement Lead

TWG Global AI•Santa Monica, CA

5d•$125,000 - $170,000•Hybrid

About The Position

At TWG Group Holdings, LLC (“TWG Global”), we drive innovation and business transformation across a range of industries—including financial services, insurance, technology, media, and sports—by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role The AI Product Enablement Lead plays a crucial role in helping enterprise teams successfully use a complex, orchestrated agentic AI assistant. This hybrid role spans user enablement, training, product collaboration, and structured feedback management . You will partner with product managers, engineers, and subject-matter experts to build AI literacy, document workflows, translate user needs into product insights, and ensure employees can use advanced multi-agent capabilities safely and effectively. The ideal candidate is a strong communicator who can simplify complexity, understand real workflows, and help shape meaningful product improvements.

Requirements

5+ years in training, enablement, L&D, product operations, technical evangelism, or a product-adjacent role.
Strong communication, facilitation, and writing skills suited for both technical and non-technical audiences.
Working understanding of LLMs, generative AI concepts, and agentic system behaviors.
Experience with user research or gathering requirements for product teams.
Strong program and content management skills with the ability to drive adoption and measure impact.
Comfortable working cross-functionally and influencing without formal authority.

Responsibilities

Training & AI Enablement Develop and maintain training content: tutorials, best-practice guides, workflow examples, safe-use playbooks, and self-service resources.
Deliver workshops, webinars, demos, and hands-on sessions to diverse audiences.
Manage internal enablement channels to support ongoing literacy and adoption.
User Research & Workflow Analysis Conduct interviews, workflow walkthroughs, and shadowing sessions to understand real employee workflows and challenges.
Document user stories, workflow maps, and requirements that clarify how people interact with agentic AI.
Identify high-value use cases and opportunities where agentic AI can streamline or augment work.
Product Collaboration & Feature Support Partner with product and engineering teams to define and refine features, write or contribute to user stories, and support prioritization.
Participate in prototype evaluations, testing sessions, and release readiness reviews.
Help design safe-use guidelines, operational guardrails, and experience patterns appropriate for multi-agent AI behavior.
Feedback Loop & Continuous Improvement Act as the primary conduit between the user community and product teams, synthesizing feedback from training sessions, support channels, and usage data.
Identify recurring friction points or misunderstandings and translate them into actionable updates for product teams or revised training content.
Maintain structured tracking of product feedback, user needs, and adoption blockers.
Program Management & Metrics Manage the end-to-end lifecycle of AI enablement programs — needs analysis, content creation, delivery, measurement, and iteration.
Track and report adoption, engagement, proficiency, and usage trends.
Provide insights to leadership on user behavior, capability gaps, and areas of improvement.