Resume

Experience

McKinsey Technology · December 2021 – Present

Led production optimization engagement with GenAI implementation at a US steel manufacturer with multiple mills, building on enterprise GenAI deployment experience to optimize production scheduling, order batching, and facility utilization; sized a ~$200M annual profit improvement opportunity
Re-evaluated a ~$35M/year ERP contract and developed a GenAI and data strategy for a Canadian oil & gas company, unlocking siloed data capabilities and building an enterprise AI roadmap; CIO presented findings to the board, expanding into follow-on work
Redesigned the technology operating model for a federal financial agency, consolidating 10+ business units and 150+ senior engineering leaders under a new horizontal governance structure across previously siloed branches
Drove ~$30M in incremental annual savings across a ~$2B infrastructure budget through compute scheduling optimization, consumption-based contract renegotiation, hardware resale, and contractor consolidation
Optimized cost-of-goods-sold for a global sports retail brand, conducting component-level pricing analysis across Asian manufacturing suppliers to identify renegotiation levers and margin improvement opportunities

July 2017 – November 2021

Led data infrastructure and executive analytics for $30B tax revenue operations; reduced reporting processing time by 90%.

Founding Engagement Manager (Client-Deployed) Confidential · McKinsey & Company · Jan 2025 – July 2025

Turned billions of dollars of static consulting deliverables into a living, AI-powered knowledge system; built and deployed the platform across 3 client sites (semiconductor, HVAC, steel) as sole business lead from inception
Drove end-to-end implementation at each client site, redesigning how teams surface, synthesize, and build on prior strategic work — from knowledge graph architecture to executive rollout
Scaled from founding team to 40–50 person cross-region operation (US, Europe, India); owned product direction and governance; transitioned platform to a dedicated team of 5+ PMs and multiple consultants for continued development

Creator, AI Context Management System Open Source · Solo-built · PyPI: ontos · Apache 2.0

Solved the context portability problem across AI tools — built a repo-native knowledge graph in markdown + YAML that makes decisions inspectable, repeatable, and durable across sessions and rewrites
Designed a structural graph traversal system with layered context (kernel → strategy → product → atom), ensuring strategic rationale survives when implementation is rewritten
Published on PyPI as a Python CLI; used in daily production workflows; 500+ commits; roadmap to MCP integration

Master of Science in Business Analytics · 2019–2021 · GPA: 3.74/4.0 · Completed while working full-time

Bachelor of Business Administration · 2016–2019 · Completed while working full-time

Build: Python, CLI tooling, Git/GitHub, CI/CD, Docker, AWS, YAML/Markdown, SQL, data pipelines
AI: Multi-agent systems, context engineering, LLM application development, LLM APIs (OpenAI, Anthropic, Google), MCP, LLM evaluation design
Operate: 0-to-1 product development, GenAI strategy, cross-functional team leadership, executive stakeholder management
Languages: English (native), Korean (bilingual)