CV

Basics

Name Amgad Madkour
Label Engineering Leader
Email amgad.madkour@gmail.com
Url http://amgadmadkour.com
Summary Engineering leader with 10+ years of experience building and shipping AI-powered products at scale. Deep expertise in Artificial Intelligence, Knowledge Graphs, Data Management, and Data Integration. Proven track record of building and leading high-performing teams from the ground up, driving roadmap alignment across organizations, and delivering measurable outcomes on products serving millions of users. Currently managing a team of Software Engineers and Applied Scientists across Microsoft's consumer AI products.

Work

  • 2022.03 - Present

    Redmond, USA

    Principal Engineering Manager
    Microsoft
    • Built a team from scratch, owning full hiring, role definition, leveling, promotions, and performance management across engineers and applied scientists.
    • Lead commerce savings in Microsoft Copilot, defining the platform architecture and technical direction for ML-driven features including product tracking, automatic coupons, cashback, and price alerts --- serving millions of users across Web, Mobile, and Edge.
    • Drove roadmap alignment across design, product, UXR, engineering, and applied science orgs as DRI to integrate core shopping scenarios into Copilot.
    • Redesigned and scaled the savings platform architecture to support multiple products and millions of users with high performance and reliability.
    • Doubled product tracking growth within six months; introduced reliability standards and quality gates that improved platform stability across the team.
    • Delivered Microsoft Autos AI Assistant --- the first generative AI-powered assistant on an automotive marketplace --- contributing to 3× DAU growth and 100% YoY revenue growth.
    • Built "My Garage" and Autos Copilot for Microsoft Autos Marketplace.
  • 2019.01 - 2022.03

    Redmond, USA

    Senior Data & Applied Scientist
    Microsoft
    • Defined the autos entity framework technical architecture adopted across Bing, MSN, and Microsoft Autos Marketplace.
    • Fine-tuned ML models for product information extraction on Microsoft Edge, improving accuracy and production reliability.
    • Designed a graph representation linking entities to news articles, powering downstream annotation and entity linking services.
    • Cut computation and storage costs for entity matching workflows by 50% through indexing and candidate generation optimizations.
  • 2006.02 - 2010.09

    Cairo, Egypt

    Research Engineer
    IBM
    • Co-invented a patented k-partite graph technique for tag recommendation during resource bookmarking.
    • Developed a spam detection system for social bookmarking using semantic features evaluated across multiple ML algorithms.
    • Built an unsupervised biomedical NLP system for extracting protein-protein interactions from scientific literature.
    • Contributed to a machine-assisted translation system using continuous space language models for statistical machine translation.
    • Collaborated with IBM Watson lab (Yorktown) on an unstructured information management platform for knowledge discovery from news.

Education

  • West Lafayette, USA

    PhD
    Purdue University
    Computer Science