How would you work with engineering to reduce latency in Advertising

Problem Statement Description

Product context: Amazon is a commerce, logistics, media, devices, and cloud company; its products include Marketplace, Prime, Prime Video, Alexa devices, ads, fulfillment, and AWS.

You are the Technical PM for Amazon Advertising experiences shown to grocery shoppers across high-intent surfaces such as search results, browse pages, product detail pages, cart, and checkout. Advertising latency has become a concern because slow ad decisioning or rendering can degrade the shopping experience, reduce conversion, and impact advertiser performance, especially in time-sensitive grocery journeys where customers expect fast discovery and checkout.

The interview is asking how you would partner with engineering to diagnose and reduce latency without compromising ad relevance, auction integrity, measurement accuracy, privacy, or marketplace trust. The scope includes understanding the end-to-end ad request path, defining latency targets, identifying bottlenecks, prioritizing technical work, and aligning stakeholders across ads, retail, infrastructure, data science, and client-side experience teams.

You should frame the problem as both a customer experience and systems reliability challenge. The expected discussion should cover how you would translate product impact into technical requirements, make trade-offs between speed and ad quality, and create an operating model for safe rollout and ongoing observability.

The experience should consider:

- The grocery shopper journey and where ad latency is most harmful, such as search, substitutions, add-to-cart, and checkout moments.

- Clear latency definitions, including client-side load time, server-side ad decisioning time, auction response time, rendering time, and tail latency such as p95 or p99.

- Key systems and dependencies, including ad ranking, bidding, targeting, catalog data, inventory availability, personalization, experimentation, logging, and downstream measurement.

- Engineering collaboration model, including ownership, service-level objectives, prioritization, dependency management, and incident response.

- Product trade-offs between faster responses, ad relevance, revenue, advertiser fairness, customer trust, and page performance.

- Data, privacy, and security requirements for using shopper context, grocery intent signals, location, availability, and personalization inputs.

- Rollout and observability needs, including instrumentation, dashboards, A/B testing, alarms, guardrails, and rollback criteria.

- Reliability expectations during peak grocery traffic, promotions, seasonal spikes, and constrained fulfillment windows.

The goal is to explain how you would lead a technically grounded, customer-obsessed latency reduction effort with engineering: defining the problem precisely, aligning on measurable outcomes, managing trade-offs, and ensuring improvements are safely delivered and sustained across Amazon Advertising surfaces.