Our Mission

Day to Day

As a Lead Learning Architect on the AI for Indeed Enablement team, you will own learning and enablement strategies that empower Indeedians to effectively use AI to help people get jobs. You will design scalable learning architectures, develop enablement frameworks, and drive execution directly or through clear delegation. You will partner with program managers who handle coordination and logistics, allowing you to focus on learning strategy, quality, and measurable impact.

The AI for Indeed Enablement team helps employees effectively adopt AI in their day-to-day work. As part of AI for Indeed within Business Technology, the team designs and scales enablement programs, guidance, and supporting frameworks that make AI practical, safe, and high impact across the company. Their work helps teams discover and use the right AI tools, build AI skills, and translate emerging capabilities into better workflows, improved outcomes, and faster progress toward helping people get jobs.

Responsibilities

• Own the learning and enablement strategy for workforce AI capabilities, translating behavior change and business objectives into clear learning outcomes, competency models, and persona-based enablement approaches.
• Design scalable, inclusive learning architectures using systems thinking to support diverse audiences and use cases; build community-driven models with peer-to-peer scaffolding and self-sustaining knowledge-sharing mechanisms.
• Develop and curate AI learning pathways and self-serve resource ecosystems (wikis, templates, decision frameworks, learning platforms) that balance guided learning, peer-generated content, and experiential practice.
• Drive enablement execution by directly creating high-impact learning experiences or delegating to subject matter experts, vendors, or community contributors.
• Establish learning measurement frameworks that track leading indicators (engagement, community participation) and lagging indicators (adoption, proficiency, behavior change, operational impact); use data to optimize programs and demonstrate ROI.
• Partner with program managers on rollout planning while maintaining ownership of learning quality, instructional integrity, and learner experience throughout execution.

Skills/Competencies

• Requires a minimum of 10 years of related experience; or a minimum of 8 years with a Bachelor’s degree; or 6 years and a Master’s degree; or a PhD with 3 years experience.
• Learning Architecture & Systems Thinking: Expertise in designing scalable learning systems that drive AI-driven workforce transformation, competency models, and community-driven enablement frameworks; ability to apply systems thinking to federated learning models with diverse audiences and modalities; applies leading and innovative change management principles to support sustained business impact
• Enablement Strategy & Execution: Ability to translate business priorities into clear learning strategies with defined outcomes and persona-based approaches; sound judgment about when to build directly vs. delegate with clear quality standards.
• Instructional Design & Inclusive Practices: Deep knowledge of adult learning principles, instructional design methodologies, and universal design; commitment to creating accessible, equitable learning experiences for diverse global audiences; Ability to implement cutting-edge experiences leveraging AI skills and agents
• Content Strategy & Curation: Experience developing learning pathways and self-serve resource ecosystems; skilled at determining what to create, curate, commission, or crowd-source to maximize impact and scalability; leverages approved AI tools and features to add speed and quality to content-building
• Learning Measurement: Proven ability to create and implement a learning measurement strategy that measures quantitative and qualitative learning outcomes; can apply data strategy and management principles to ensure availability and quality; experience create data-driven insights on the learning program’s impact on AI-driven business KRs and KPIs
• AI & Technology Fluency: Proficiency with AI tools and concepts; ability to quickly learn new capabilities and translate technical features into practical learning applications and use cases.

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