Sr Manager, Applied Science, Alexa for Shopping (rufus)

Amazon Amazon · Big Tech · Palo Alto, CA · Applied Science

Senior Manager, Applied Science at Amazon for Alexa Shopping, leading teams to build and scale next-generation conversational AI and multi-agent systems. Focuses on LLMs, agent orchestration, retrieval, grounding, evaluation, and AI infrastructure, with responsibilities spanning technical strategy, product partnership, and end-to-end delivery of production AI systems.

What you'd actually do

  1. Lead and grow teams of Applied Scientists and Machine Learning Engineers working on conversational AI and multi-agent orchestration systems.
  2. Define and drive technical strategy for large-scale generative AI systems, including LLM routing, prompting, grounding, memory, tool use, personalization, and response optimization.
  3. Partner closely with Product, Engineering, and Tech leadership to align AI investments with long-term business and customer goals.
  4. Drive end-to-end delivery of production AI systems balancing quality, latency, scalability, safety, and operational reliability.
  5. Establish scientific and engineering best practices across experimentation, evaluation, model iteration, and production deployment.

Skills

Required

  • 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
  • Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
  • Experience building large-scale machine learning and AI solutions at Internet scale
  • Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
  • Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

Nice to have

  • 10+ years of practical work applying ML to solve complex problems for large-scale applications experience
  • 5+ years of hands-on work in big data, machine learning and predictive modeling experience
  • 5+ years of people management experience
  • PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
  • Experience in practical work applying ML to solve complex problems for large scale applications
  • Experience working with big data, machine learning and predictive modeling
  • Experience in people management
  • Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
  • Experience with Java, C++, or other programming language, as well as with R, MATLAB, Python, or an equivalent scripting language
  • Experience researching actual applications

What the JD emphasized

  • building next-generation conversational AI and multi-agent systems
  • large-scale generative AI systems
  • end-to-end delivery of production AI systems
  • scalable evaluation methodologies and quality frameworks

Other signals

  • building next-generation conversational AI and multi-agent systems
  • driving scientific innovation and execution across large language models (LLMs), agent orchestration, retrieval and grounding systems, evaluation frameworks, and scalable AI infrastructure
  • delivering measurable customer impact through applied machine learning and generative AI technologies
  • end-to-end delivery of production AI systems balancing quality, latency, scalability, safety, and operational reliability
  • scalable evaluation methodologies and quality frameworks