Seattle, WA

Kene Ezeoke

0-to-1 Builder, Operator, Program Leader

Joined a NYC startup as employee #13, closed the deals that proved product-market fit, built the team from 1 to 6, and helped attract investment from Marc Benioff. Since then, 8+ years across Amazon, Apple, Google, and F5 doing the same thing in different contexts: walking into ambiguity, building what doesn't exist, and making the results visible to the people who matter. I work best when the problem isn't fully defined yet. Chicago Booth MBA. Most recently, designing and deploying production ML models (forecasting and NLP classification) solo, with AI as the build team.

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Where I've built
Amazon Apple F5 Networks Google Silverline
8+
Years in Big Tech
$45MM
Revenue driven at F5
$500MM
Revenue managed at Apple
40%
YoY Revenue growth at Amazon
50%
Faster launch cycles

Experience

Sr Program Manager
Amazon
Jul 2024 – Present
Seattle, WA
Business performance and executive reporting | Add to Delivery
  • Built the business performance metrics program from scratch, standardizing reporting across 3 orgs and 4 partner teams. Program insights now reach Amazon board meetings and earnings calls.
  • Support the annual goal-setting process for Add to Delivery, contributing performance analysis and drafting sections of OP1/OP2 goal documents. Own the ongoing tracking cadence through monthly goal updates that roll into VP and S-team reporting, coordinate submission timelines across senior managers, and support QBRs with metrics reviews and performance callouts.
  • Designed and launched a GenAI reporting automation system using RAG architecture, writing the business logic and context engineering framework that enables LLMs to interpret performance data across multiple internal data sources. Built an LLM-as-a-judge AI scorecard to track quality week over week. Delivers weekly automated dashboards now used in VP-level reviews.
  • Built and deployed a CatBoost forecasting model for weekly metric noise classification, enabling the WBR process to automatically distinguish normal fluctuations from signals requiring investigation. Selected by cross-team consensus over competing approaches.
  • Built the VOC program from scratch, including a custom API tool that cut transcript collection from 4-6 hours to 15 minutes and a hybrid ML classification pipeline (sentence-transformer embeddings + keyword disambiguation) that reduced unclassified contacts from 22% to 9% and powers leadership MBR reporting. Analysis surfaced the duplicate order pattern that drove a product redesign and a new launch criteria metric. Program scales to 6 international markets with no added headcount or engineering resources.
  • Authored monthly executive business performance narratives analyzing business trends and metric movements, translating insights into prioritization recommendations. Drove product reprioritization, resulting in 1.6% reduction in customer cancellations and 1.2% reduction in return rates.

Tools & Expertise

AI & Automation
NLP / Text Classification Sentence-Transformer Embeddings Time Series Forecasting Prophet Chronos 2 CatBoost RAG LLM Evaluation & Scoring Context Engineering Prompt Engineering AI-Assisted Development Workflow Automation
Data & Analysis
SQL Advanced Excel Tableau QuickSight LLM-Powered Dashboards
Program Management
Lean Six Sigma Green Belt Stage-Gate / PDLC LucidChart Miro Mural Smartsheet Asana Confluence SharePoint
CRM & Customer Experience
Salesforce Sales Cloud Salesforce Service Cloud HubSpot Qualtrics

Education

Chicago Booth
MBA
Stony Brook University
BSc

Let's connect.

If you're working on something interesting and think my background is a fit, I'd love to hear about it.

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