Reddit Staff Software Engineer Interview Questions

1.Tell me about a time your system got hammered by unexpected traffic. Walk me through what broke, how you responded, and what you changed so it wouldn't happen again.

2.Tell me about the most pragmatic — maybe even ugly — fix you've shipped at production scale. What made you choose it over doing it 'right,' and do you stand by that call?

3.Tell me about a time you made a technical decision that you knew would affect a specific user community, not just metrics. What was the tradeoff, and how did you weigh it?

4.Tell me about a time you fought for a feature or design choice specifically because it protected user anonymity or expression — even when there was internal pressure to water it down.

5.Walk me through a system you designed or hardened specifically because you expected adversarial behavior. What attack vectors were you thinking about, and where did you end up being wrong?

6.Tell me about a time you led a major architectural change — migration, redesign, or decomposition — while keeping a high-traffic production system live. What was the hardest part, and what would you do differently?

7.Reddit's feed ranking runs on Kafka. If a downstream consumer starts lagging and the lag grows unbounded, how do you detect it, and what levers do you pull to recover without dropping events?

8.You're adding a new field to a gRPC service contract that's consumed by a dozen other microservices. How do you roll this out without breaking anything, and what's your process for deprecating the old field eventually?

9.Reddit's GraphQL federation gateway stitches together schemas from multiple subgraph services. If a single slow subgraph is causing P99 latency to spike on the gateway for queries that don't even touch that subgraph, what's happening and how do you fix it?

10.We run A/B experiments across Reddit's feed ranking, but some subreddits are small enough that they can't reach statistical significance in a standard experiment. How would you design the experimentation platform to handle low-traffic communities without either waiting months for results or making decisions on noisy data?

11.Reddit's vote counts are read-heavy and written constantly. If you had to redesign how vote counts are stored and served to eliminate the write bottleneck on PostgreSQL at peak traffic, what would your architecture look like and what consistency tradeoffs are you willing to accept?

12.You're a Staff Engineer owning Reddit's public data API. A large AI company wants to dramatically increase their data access volume for LLM training — well beyond current rate limits. Walk me through how you'd evaluate and architect a tiered access model that serves that use case while protecting the platform and the communities that created the content.

13.Design a system that lets Reddit moderators configure and enforce subreddit-specific AutoModerator rules at scale. Today a single viral post can trigger millions of comment submissions in minutes — your system needs to evaluate every one of them against potentially hundreds of rules without falling over.

14.Reddit's search needs to index posts and comments in near real-time — when something goes viral, it should be findable within seconds of being posted. Walk me through how you'd design that ingestion and indexing pipeline.

15.Design Reddit's ad auction and delivery system for a single ad impression — from the moment a feed request comes in to when we decide which ad to show, in under 100ms. Assume millions of requests per minute at peak.

16.Reddit wants to recommend subreddits to new users during onboarding to help them find their communities. Design the recommendation system — from data signals to serving — keeping in mind that a bad first-day experience is the single biggest driver of user churn.

17.Design a cross-subreddit content similarity system that can detect when the same image or video is reposted across communities — not just exact duplicates, but near-duplicates with crops, filters, or re-encodings applied. This needs to run at Reddit's full content ingestion volume.

18.Reddit's comment ranking system needs to run per-request for every thread view, but comment threads on viral posts can have hundreds of thousands of comments. Walk me through how you'd design the ranking and pagination system so that P99 thread load times stay under 500ms even on threads that size.

19.Tell me about a time you had to align multiple engineering teams around a shared technical standard or platform decision. How did you get people on board who didn't report to you?

20.Describe a time you pushed back on a product or business requirement because you believed it would harm your users or communities. What happened?

21.Tell me about a time you sponsored or actively advocated for a more junior engineer from an underrepresented background — not just mentored them, but put your reputation behind them. What did that look like in practice?

22.You've identified a systemic reliability problem — maybe it's a class of incidents that keeps recurring across teams — but fixing it requires changing how multiple teams build their services. Nobody owns the problem. How do you drive that kind of cross-cutting change at Reddit's scale?

23.Tell me about a time you had to make a call on a high-stakes technical decision under real time pressure — not enough data, not enough consensus — and you turned out to be wrong. How did you handle the aftermath?

24.You're a Staff Engineer on a team that's been quietly accumulating technical debt for two years — the kind that's slowing every new feature to a crawl. Product wants a full roadmap of new features. How do you negotiate that tension, and what does your actual plan look like?

25.Estimate how many comments are posted on Reddit in a single day. Walk me through your assumptions.

26.Reddit's logged-out traffic is a huge part of total pageviews — people searching Google and landing on threads. How would you think about the revenue opportunity from that logged-out surface, and what's the biggest constraint?

27.Reddit's Awards and Coins system was sunset. Assume you're post-mortem-ing the decision — how would you structure the analysis of whether sunsetting it was the right call, and what metrics would be the most contested?

28.Moderators on large subreddits sometimes go on strike or set communities to private to protest platform decisions. If you were quantifying the business impact of a coordinated mod strike, how would you structure that analysis?

29.Reddit is considering expanding aggressively into a new international market — say, a large Southeast Asian country. How would you estimate the engineering investment required, and what Reddit-specific risks would you call out that you wouldn't flag for a generic SaaS company?

30.Reddit's feed ranking serves billions of requests per day, but the ranking model is also used to decide which content gets amplified to millions of users. If the model develops a systematic bias — say, it's underranking posts from smaller or newer communities — how would you detect it, quantify the harm, and decide when it's severe enough to act on?