Held full storefront scope through a 4-team consolidation
Problem: A major layoff and org restructure collapsed four frontend teams — UFO, Search, PDP, and Conversion — into one while keeping the same ownership surface across two storefronts.
Action: Stepped into consolidated leadership, re-prioritized around highest-leverage surfaces, extended capacity with an offshore contract team, and maintained delivery across commerce, campaigns, experimentation, analytics, and CMS.
Outcome: [Add metric tomorrow: deploy cadence, sprint velocity, or scope-retention proof with headcount numbers.]
Tech: React, Statsig, ContentStack, Bitbucket, Jira.
Scaled experimentation across two high-traffic storefronts
Problem: The frontend needed a reliable way to test changes on BBBY and buybuy BABY without regressions or guesswork at scale.
Action: Built out and maintained Statsig as the site-testing and experimentation layer — A/B manifests, activeSiteTestMap, experiment cleanup, and cross-surface rollout across PDP, PLP, Homepage, and Page Triggers.
Outcome: [Add metric tomorrow: a conversion lift, revenue-per-visit impact, or number of experiments shipped in a period.]
Tech: Statsig, React, ContentStack.
Built AI engineering infrastructure for the frontend team
Problem: Developers were using AI tools ad hoc with no shared workflows, skill frameworks, or documentation — leaving productivity gains on the table as the team got leaner.
Action: Created byon-skills, a reusable AI skill framework covering development, QA, and code-review workflows. Authored an AI Hub, developer guides, Atlassian/Bitbucket/Jira/Confluence integration docs, and AI landscape and terminology material for the team.
Outcome: Gave a lean team shared AI workflows and onboarding paths — turning individual experimentation into repeatable, team-level infrastructure at a moment when headcount was shrinking.
Tech: Claude, Cursor, Atlassian MCP integrations, byon-skills framework.