Enterprise Systems, Knowledge Infrastructure, and Platform Strategy
I design scalable operational and information systems that help engineering and enterprise organizations discover, govern, reuse, and operationalize trusted knowledge at scale.
My work sits at the intersection of platform strategy, information architecture, governance systems, developer enablement, workflow orchestration, and AI-enabled operational infrastructure. Across Amazon, AWS, Meta, and Warner Bros. Discovery, I have led initiatives that reduce operational fragmentation, modernize enterprise knowledge ecosystems, improve interoperability across systems, and build frameworks that increase organizational capability.
I specialize in transforming disconnected workflows and fragmented repositories into durable platform ecosystems designed for discoverability, maintainability, governance, and long-term scalability.
Platform ecosystems, interoperability, and cross-team operations.
Structured content, metadata, taxonomy, and reusable knowledge.
Operating models, lifecycle standards, and automation foundations.
Documentation, onboarding, and self-service tooling.
Metadata enrichment, retrieval, and trusted AI workflows.
I approach organizations as interconnected systems, not isolated tools or departments. The work usually begins with understanding the outcome the organization is trying to achieve, then identifying where information flow breaks down, where operational friction accumulates, where teams duplicate effort, and where governance gaps create long-term complexity.
From there, I design operating models, platform architectures, and governance structures that simplify workflows, improve interoperability, and help organizations scale more coherently. My work spans structured content architecture, metadata and taxonomy systems, enterprise search, API-connected ecosystems, lifecycle management, workflow automation, AI-assisted knowledge systems, and developer/documentation operations.
Employees reached through global knowledge architecture.
Reduction in transcription-processing costs through AI workflow optimization.
System availability delivered through AWS platform modernization.
Adopted a relaunched AWS enterprise knowledge platform.
I lead strategy and operational direction for an enterprise multimedia platform ecosystem spanning content governance, metadata architecture, AI enrichment workflows, lifecycle management, and interoperability planning across multiple organizations. In this role, I guide platform strategy, roadmap direction, operating model decisions, and cross-functional execution across engineering, program management, and information operations. Managed assets expanded from 109K to 195K, governed collections grew from 380 to 830, and AI-assisted workflows using transcription, sentiment analysis, video object detection, and automation reduced transcription-processing costs by 90%.
I designed and implemented structured-content architecture for a global enterprise knowledge ecosystem serving 1.5M+ employees across multiple content domains and delivery channels. My work focused on reusable metadata, governance frameworks, AI-assisted retrieval, machine-readable policy systems, scalable knowledge reuse, and enterprise discoverability. I also developed content-model visualization and validation tooling integrated into CI/CD workflows and enterprise CMS APIs, improving governance consistency and long-term content-model maintainability.
I led enterprise-scale knowledge strategy for Meta Infrastructure Data Center organizations supporting more than 10K employees across five operational groups. The organization was fragmented across more than 100 documentation systems and disconnected workflows, so my work focused on repository governance, discoverability, reuse, operational standards, and future-state retrieval modernization. I managed a four-person team and a $2M operational budget supporting document-management services, platform planning, and governance standardization.
I led an engineering enablement and technical learning organization responsible for onboarding systems, documentation workflows, and scalable knowledge delivery. I shifted onboarding away from one-to-one knowledge transfer toward modular, self-service systems, moving more than 60% of prior onboarding time into scalable documentation and enablement while achieving 100% first-30-day compliance. I also created an engineering knowledge hub with IT and Global Security, reducing onboarding tickets by 50%, reducing time to access by 25%, and cutting documentation production time from two months to one.
I led the transformation of an internal Content Services Platform supporting AWS documentation and enablement organizations, repositioning it as a governed and reusable enterprise knowledge ecosystem. I directed platform modernization, governance redesign, API restoration, operational stabilization, and roadmap strategy across modular publishing systems, automation workflows, and machine-learning-assisted governance. The relaunch improved platform availability from 98% to 99.99%, grew monthly active users from 10K to 25K, raised customer satisfaction from 60% to more than 85%, expanded adoption across 110+ teams, and improved search efficiency by approximately 15%.
I built scalable internal machine-learning course operations and reusable technical content delivery systems. This included opening remote classroom infrastructure across global locations and developing video-based engineering education content with Amazon machine learning subject-matter experts. This work strengthened my approach to modular knowledge delivery, distributed enablement, and operational scaling.
I launched and governed two digital asset-management systems for Microsoft Retail, structuring metadata, taxonomy, permissions, and search across more than 80K assets. This role formed an early foundation in metadata systems, digital asset governance, enterprise search, permissions design, and reusable content operations.
Repositories are private. Selected artifacts are available upon request.
Deck Companion is a full-stack operational platform exploring deployment workflows, observability, authentication, CI/CD pipelines, operational readiness, and production-oriented software practices.
It is my most complete personal example of building and maintaining a software product end to end, and it reflects my interest in bridging product thinking, technical implementation, and operational reliability.
Archivum is a media-ingestion and archival system designed around verification, deduplication, manifest tracking, inventory integrity, and long-term preservation workflows.
The project connects my long-standing work in metadata, digital asset management, and archival systems with hands-on systems development.
Resume Builder is a structured career-evidence and retrieval system using linked records, governance workflows, and AI-assisted synthesis to generate validated, role-specific professional outputs.
It applies information architecture, knowledge-graph thinking, Git-based documentation practice, and AI-assisted synthesis to a real personal information system.
I believe organizations scale through operational clarity, interoperable systems, durable governance, and accessible institutional knowledge.
The best systems reduce cognitive overhead, simplify complexity, and help teams work at higher leverage. My focus is not simply managing information, but designing ecosystems that allow organizations to think, operate, and scale more coherently.
My interests outside of work reinforce the same systems orientation that drives my professional work.
I maintain a personal lab environment to learn more about hosting, deployments, observability, storage, networking, and operational reliability. I am also interested in archival integrity, metadata strategy, long-term digital preservation, photography, and writing as a way to clarify ideas and turn curiosity into systems I can build and test.