Sr. Mgr., Software Development, Whole Page Construction

Amazon Amazon · Big Tech · Seattle, WA · Software Development

Senior Manager, Software Development for Prime Video's Whole Page Construction team, leading engineering teams to build real-time, AI-driven personalized storefront systems. The role involves partnering with applied scientists and product managers to scale and automate content discovery using ranking models and generative AI, impacting over 100 million customers globally.

What you'd actually do

  1. lead multiple engineering teams building the real-time page construction systems that powers Prime Video's homepage worldwide
  2. partner closely with applied scientists designing novel ranking models, product managers defining the future of content discovery, and business leaders across Studios, Sports, and Channels
  3. drive technical strategy, develop senior engineering talent, and shape how automation and business intent coexist in at Amazon scale
  4. building ML-driven understanding about customers' preferences based on their past engagement, current context (e.g. device, title release date etc.) and other signals (e.g. search activity etc.)
  5. operate in a complex business/tech space requiring us to operate at speed and rapidly prototype/experiment

Skills

Required

  • 10+ years of engineering experience
  • 5+ years of engineering team management experience
  • 10+ years of planning, designing, developing and delivering consumer software experience
  • Experience managing multiple concurrent programs, projects and development teams in an Agile environment
  • Experience partnering with product or program management teams
  • machine learning
  • statistics
  • deep learning
  • natural language processing
  • information retrieval

Nice to have

  • Experience designing and developing large scale, high-traffic applications
  • Bachelor's degree in computer science, computer engineering, or related technical field
  • Experience with AWS products and services

What the JD emphasized

  • scaling and automating manual editorial curation with fully autonomous page assembly powered by state of the art ranking models and generative AI
  • partner closely with applied scientists designing novel ranking models
  • ML-driven understanding about customers' preferences
  • operate at speed and rapidly prototype/experiment

Other signals

  • AI-driven systems
  • state of the art ranking models
  • generative AI
  • ML-driven understanding
  • content discovery experience