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Entry-level prep for Amazon's SDE I loop - coding fundamentals plus Leadership Principles, scaled to a new-grad bar.
Amazon SDE I is the entry-level new-grad rung at AWS, retail, ads, and devices. The loop is similar to SDE II but the technical bar is dialed back: coding rounds are Easy-to-Medium with emphasis on working code and edge cases rather than deep optimization, and system design is typically not part of the loop (or appears as a very bounded design conversation, not a full round). The Leadership Principles still matter - and significantly so. Even at SDE I, expect 2-3 LP questions per round, including a Bar Raiser who probes deep on a smaller set of principles. New grads can use school projects, internships, and side projects for STAR stories - what counts is specificity, not enterprise scope. Recent stories (last 12-18 months) score better than older ones.
Amazon's behavioral bar applies even at SDE I. Have one strong STAR story per Leadership Principle - school projects and internships are valid sources. Recent stories (last 12-18 months) score higher.
Easy-to-Medium difficulty. Cleanliness and edge cases beat raw optimization. Strings, arrays, hash maps, basic trees, BFS/DFS - the workhorses.
Hash maps, queues, stacks, trees. Amazon's coding rounds at SDE I lean heavily on these. Know your tree traversals cold.
Sometimes appears in a coding round (parking lot, library system). Clean class boundaries and reasonable interfaces are enough at SDE I.
Not always required at SDE I. If it appears, expect a very bounded design conversation - URL shortener, basic notification system - with the interviewer guiding actively.
Comes up if system design appears - DynamoDB-style thinking, partition keys, basic indexing. SQL basics enough for most SDE I loops.
Curated walkthroughs for the bounded designs that show up in Amazon's system design rounds. Capacity estimation, architecture, deep-dives, and trade-offs.
The canonical bounded system design problem. Read-heavy, hot-key prone, and a great vehicle for hashing, caching, and capacity estimation.
Five algorithms, three sharding strategies, one fail-open vs fail-closed decision. The bounded design that surfaces in every backend interview loop.
Sample STAR answers, common prompts, pitfalls, and follow-up strategies for the behavioral themes that decide Amazon's loop.
The most-asked Amazon LP. Interviewers screen for evidence you reasoned about end-user impact, not just shipped a feature.
Tested at every level, scored harder at senior. Did you take responsibility for outcomes - or just for tasks?
Speed matters. But the principle is reversible-vs-irreversible reasoning, not 'I work fast.' Get this distinction wrong and the answer reads as reckless.
Microsoft's Growth Mindset core. Also tested at Google, Anthropic, and any company that screens for self-awareness. The signal is whether you actually changed.
Total comp ranges, base, equity, and bonus across the levels tested in this loop. Aggregated from public sources.
5 SWE levels covered. Updated 2026-05.
357 MCQs and 237 coding challenges, grouped by topic. Free preview shows question titles - premium unlocks full content.
Behavioral and system design rounds reward practice with a live AI interviewer that probes follow-ups, not silent reading.
Start an AI mock interview →Very important. Amazon does not skip behavioral signal at any level. The bar is calibrated to what's reasonable for a new grad - school projects, internships, hackathons, and side projects all count as STAR material - but the framing must still be specific. 'I worked on a team project' is below bar. 'In our distributed systems class final project, our team disagreed about consistency model; I proposed running an experiment with both approaches and we picked based on data' is in range.
Yes. Bar Raiser is part of every Amazon onsite loop, including SDE I. They're calibrating against Amazon's overall hiring bar, not just team needs. Coding is lighter than at SDE II but Leadership Principle probing is just as deep. Don't assume the round is easier because you're new grad.
Use school projects (especially group projects), internships, hackathons, club leadership, side projects, and even significant volunteer or part-time work. Pick 6-8 specific incidents and identify which 2-3 Leadership Principles each demonstrates. Practice telling each in 90 seconds: Situation, Task, Action (heavy on this), Result with metrics where possible.
Usually not as a standalone round. Some loops include a bounded design discussion - 'how would you design a service that does X' - within a coding round, but you won't face a full 60-minute design round at SDE I. Knowing system design vocabulary (caching, load balancers, databases) is useful background.
All three are entry-level new grad rungs targeting 0-2 YOE. The technical bar is similar - Medium difficulty coding with edge cases and clean code. The behavioral bar is where Amazon stands out: even at SDE I, Leadership Principles are heavily probed, including by the Bar Raiser. Google's Googleyness round is structured but lighter at L3; Meta's behavioral signal is also lighter at E3 than at higher levels.
Often yes. Strong intern performance reviews can lead to a return offer with a shortened loop - sometimes a single 'conversion' interview. New grads coming from non-Amazon internships go through the full SDE I loop.