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Ship production LLM-powered features for Google's Commerce/Shopping platform serving over a billion shopping queries a day

Google Commerce is hiring a software engineer to design, build, test, and deploy software for the shopping experiences that serve over a billion queries a day, spanning inspiration through checkout. The JD explicitly requires production experience deploying LLM-based systems and ML/Generative AI exposure, layered on Google's standard 2-year SWE bar - expect Google's typical coding + system design + googleyness/leadership loop.

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Likely format

Google's well-known hiring process typically includes a phone screen with coding, followed by an onsite loop of coding, system design/architecture, and Googleyness/leadership interviews.

What this interview tests

  • Data structures & algorithms (Google's standard coding bar)
  • Production experience deploying LLM-based systems; ML/Generative AI quality evaluation
  • System design for high-traffic consumer commerce features (search, recommendations, checkout)
  • Code review practices and design-review leadership
  • Debugging/triaging production issues across hardware, network, and service layers

Common question themes

Coding: solve a data structures/algorithms problem and discuss complexity trade-offs

Describe an LLM-based feature you shipped to production - how did you evaluate and improve its quality?

System design: design a component of a high-scale shopping experience (e.g., product search or checkout)

How do you conduct a code review - what do you look for in style, testability, and efficiency?

Walk through triaging a production issue: how do you isolate whether it's a hardware, network, or service problem?

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