Learning Infrastructure · Workforce Development
I build the learning infrastructure that unlocks economic mobility for the workforce — at scale, with intention.
I'm a learning strategist and workforce development leader who treats L&D as infrastructure — not programming. For over a decade, I've built the systems, frameworks, and cultures that help organizations grow their people with the same rigor they apply to operations.
My work spans manufacturing, logistics, healthcare, and biosciences. At Amazon RME, I own the learning infrastructure for 40,000+ frontline automation technicians across global robotics operations. Before that, I spent five years at McChrystal Group in management consulting, where I learned to design for complexity.
The thread running through everything I do: creating economic mobility for workers who don't always have obvious advocates. That conviction shapes how I design programs, choose tools, and build teams.
I'm a 2024 Aspen Institute Education and Career Mobility Fellow — part of a network of leaders reimagining how education connects to economic opportunity.
2024 Aspen Institute Education & Career Mobility Fellow
Learning Architecture · Skills Taxonomy · Train-the-Trainer · LMS/LXP Strategy · Competency Frameworks
McChrystal Group · Amazon RME · Manufacturing · Healthcare · Biosciences
Amazon RME
Designed and own the learning infrastructure serving 40,000+ frontline automation technicians across Amazon's global robotics operations — spanning curriculum architecture, delivery systems, and technical skills frameworks.
L&D Strategy
Built a large-scale train-the-trainer program and technical training sprint architecture — including load-balanced scheduling across 17 subjects, 500+ sessions, and global trainer coordination.
Skills Infrastructure
Built Amazon RME's first enterprise skills taxonomy — creating the foundational infrastructure for baseline assessments, role-based competency frameworks, and personalized learning journeys at scale.
McChrystal Group
Five years of management consulting working with complex organizations on leadership, culture, and performance. Specialized in designing for ambiguity and building adaptive team structures.
Platform Strategy
Conducted comprehensive learning technology competitive analysis and stakeholder pitch development — aligning platform capabilities to workforce development strategy and business outcomes.
Thought Leadership
Developing a media platform and newsletter focused on workforce development and economic mobility — offering frameworks for the leaders and organizations navigating the future of work.
Three examples of the kind of infrastructure-first thinking I bring to every engagement — each one a real problem, a structured approach, and a measurable result.
Amazon RME · Global Scale
A global robotics organization with 40,000+ frontline automation technicians had no unified learning infrastructure. Field directors reported that programs were not adaptive, skills gaps were unmeasured, and training delivery was inconsistent across sites. A 65-person learning team was stretched impossibly thin.
Architected a full learning ecosystem redesign grounded in Bloom's Taxonomy and Kirkpatrick's Four Levels of Evaluation. Built a skills taxonomy and role-based competency framework. Designed a large-scale train-the-trainer program and load-balanced scheduling infrastructure across 17 technical subjects and 500+ sessions. Aligned delivery to site-level capacity and trainer availability using custom Excel tooling — practical infrastructure that could be owned by the field, not just the central team.
The organization now has a structured, measurable, and scalable learning foundation. Directors gained visibility into technician progress tied to role expectations and tenure. Training delivery became consistent and schedulable. The program created the baseline for ongoing assessment and competency tracking — shifting learning from a one-off event to a continuous infrastructure.
Amazon RME · Foundational Infrastructure
The organization had no common language for skills. Without a shared taxonomy, there was no way to run meaningful baseline assessments, build role-based learning journeys, or measure technician development over time. Training existed — but it wasn't connected to anything. Personalization at scale was impossible without first answering a more fundamental question: what skills does this workforce actually need, and how do we define them?
Built the organization's first enterprise skills taxonomy from the ground up — defining skill nodes, levels of proficiency, and role-based expectations across the automation technician population. Conducted deep discovery with subject matter experts, field directors, and technical leads to validate taxonomy structure against real job demands. Designed the taxonomy to serve as the connective tissue between baseline assessments and personalized learning journeys — so that where a technician scored on an assessment directly informed what learning path they entered. Aligned the taxonomy across multiple business units to create a single shared infrastructure rather than siloed definitions.
The skills taxonomy became the foundational layer of the organization's learning infrastructure — enabling baseline assessments, structured development paths, and competency tracking for the first time. It gave the organization a shared language for workforce capability that directors, managers, and technicians could all use. Every learning journey, assessment, and platform evaluation built afterward was grounded in this taxonomy.
Amazon RME · Platform Strategy
Leadership needed to make a high-stakes platform investment decision — but lacked the internal framework to evaluate LMS and LXP options against actual organizational needs. Existing tools were creating compliance burdens without learning outcomes. Vendors were pitching features without connecting them to workforce development strategy.
Built a comprehensive competitive analysis framework evaluating 8+ platforms (LMS, LXP, and Education-as-a-Benefit) across 500+ capability criteria — organized by learner experience, manager tools, admin capabilities, analytics, and integration. Grounded the evaluation in the organization's skills taxonomy and role-based development model. Developed a stakeholder pitch connecting platform capabilities to specific business outcomes: technician proficiency rates, time-to-competency, internal mobility, and safety compliance. Presented to directors and senior leadership with ROI projections tied to measurable workforce metrics.
Leadership had a clear, defensible framework for platform selection aligned to workforce strategy rather than vendor marketing. The analysis surfaced capability gaps in incumbent tools and created alignment across stakeholders who had previously disagreed on priorities. The pitch connected learning investment directly to operational outcomes — shifting the conversation from L&D cost to workforce infrastructure ROI.
Whether you're building a learning function, evaluating a platform, or thinking through workforce strategy — I'd love to hear what you're working on.