Amazon

Insider: Amazon (USA) 2025 Graduate Software-Engineer Openings — Salary Bands, Application Strategy & Assessment Tips for International Applicants.

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Landing a graduate software engineer role at Amazon in the USA is competitive—but extremely rewarding. For international applicants, it adds layers: understanding salary expectations, securing visa/work-authorization, mastering Amazon’s hiring process, and preparing for assessments and interviews that test both technical and behavioral skills. As of 2025, there is enough public and crowdsourced data to pull together realistic expectations and practical strategies.

Salary Bands: What to Expect for Graduate (New-Grad / Entry-Level) Role

First, let’s clarify what “graduate” typically means: a new bachelor’s or master’s graduate (0–2 years of professional experience), possibly some internships; for Amazon USA, this would mostly correspond to Level 4 (SDE I) roles.

Here’s a summary of what compensation looks like for entry‐level vs higher levels, pulled from recent data (Levels.fyi, SalarySolver etc.):

Role / Level Base Salary (approx) Stock / RSUs (first year average) Bonus (yearly) Total Comp (1st year)
SDE I (L4, New Grad / Entry-Level) ~$130,000-$150,000 base, depending on location (e.g. Seattle, Bay Area tends higher) (Levels.fyi) ~$25,000-$35,000 in RSUs (vesting over years) (Levels.fyi) ~$5,000-$10,000 typical annual / performance bonus for L4 in many places (Levels.fyi) Total around $165,000-$190,000 or more in high cost of living areas in the first year (base + RSU + bonus) (pathvira)
Mid Level (e.g. SDE II, L5) ~$170,000-$200,000+ base RSUs much higher: often ~$90,000+ yearly grants (vested over time) (pathvira) Bonus tends to be modest (but meaningful) in addition Total compensation often in the $250,000-$320,000+ range depending on location and team (pathvira)

Key Notes:

  • “Base salary” is the fixed cash salary.
  • RSUs = Restricted Stock Units. These are portions of Amazon stock granted at hire, vesting over time (commonly over 4 years). Their value depends heavily on stock performance.
  • Bonuses are less influential at new grad levels but can add a nontrivial amount.

For international applicants, cost of living in the U.S. location, visa / tax implications, and company policies (e.g. relocation / equity grants) may affect negotiations or what the offer is worth net.

Amazon’s Process & Application Strategy for Graduate SDE Roles

To maximize your chances, you need to understand how Amazon hires its graduate/new grad SDEs and plan accordingly.

The typical hiring workflow

Here’s how the application and interview process generally looks for Graduate / New-Grad SDE (USA / also similarly globally):

  1. Online Application
    Apply via Amazon.jobs or through university recruiting events. Ensure your resume is clean, relevant, emphasizes coding, internships, projects, etc.
  2. Online Assessment (OA)
    If your application is selected, you’ll often be asked to complete one or more online assessments. These are timed, virtual, and test coding and possibly logical reasoning / work style. (amazon.jobs)
  3. Recruiter / Phone Screen
    After passing the OA, there may be a screening call: to assess fit, motivations (“why Amazon?”), and sometimes a quick coding or algorithmic question. May also cover behavioral questions. (Interview Kickstart)
  4. Interview Loop / Onsite (or virtual)
    If you pass the screen, you’ll have a set (loop) of interviews. For entry level, these usually include:

    • Technical coding: solving algorithm & data structure problems
    • Possibly system design at a lighter scale (depends on team)
    • Behavioral interviews focused on Amazon’s Leadership Principles (LPs)
    • Some teams may test debugging, or interact with “work simulation” or problem scenarios. (amazon.jobs)
  5. Offer & Negotiation
    Once you pass interviews, Amazon will send an offer. For international candidates, the offer may be conditional on work authorization (visa), having degree/diploma completed, etc.
  6. Visa / Work Authorization / Onboarding
    If you’re not a U.S. citizen or permanent resident, you’ll need a visa (e.g. H-1B, OPT (for F-1 students), or some other work permit). This can slow things down. Ensuring you understand what documentation Amazon requires is vital.

Key Insights & Tips for International Applicants

Here are what tend to make a difference when non-U.S. citizens / international applicants apply to Amazon graduate SDE roles.

What the company looks for

  • Strong foundation in algorithms & data structures. Practice is essential (LeetCode, HackerRank, etc.).
  • Clear coding style, correctness, and ability to explain your reasoning.
  • Understanding the basics of system behavior, handling edge cases, performance (time/space complexity).
  • Behavioral qualities: leadership, willingness to learn, ability to handle ambiguity, customer-centric thinking (Amazon’s Leadership Principles are very important).
  • Projects/internships that show you can work with code in teams, handle deadlines, maybe even open source or prestigious competitions.

What can make or break you

Factor Strong Impact Why / Examples
Resume & Demonstrated Experience Projects, internships, contributions to real software, open source, or relevant job experience makes you standout. If you can show something you built / shipped, even if small, that shows initiative.
Coding Interview Skills High — ability to solve problems efficiently under time pressure, with clean code. Practice with timed challenges matters. Mistakes often in sloppy edge cases.
Behavioral Skills / Fit Medium-High — Amazon weighs culture fit and leadership quite seriously. You’ll often be asked things like “tell me about a time…” etc. Use the STAR method.
Communication Skills Very important for international applicants. Clarity, ability to ask clarifying questions, explaining reasoning are all evaluated.
Visa / Timing Constraints Could be a hurdle. If you don’t have degree yet, or need work permit, or there is seasonal visa cap (H-1B) etc, that may complicate or delay.

Application timing & handling delays

  • Apply early: Many University / New Grad roles have set windows; sometimes job postings close after they fill.
  • Monitor internal & external deadlines. Some assessments might have tight windows.
  • Be patient but polite in follow-ups. Sometimes assessments are passed but recruiters are busy.
  • Leverage referrals if possible (university alumni, Amazon employees). They can help surface your application.

For visa / documentation

  • Be very clear on your visa status in your application (if they ask). If working under OPT or similar, ensure you can provide proof.
  • Check whether Amazon will sponsor your visa. Many grad roles do, but not always—depends on the team, location, etc.
  • Ensure that your degree will be completed by the time Amazon wants you to start. Offers are often contingent on degree completion.

Assessment & Interview Tips

Here are actionable prepping tips that reflect what Amazon (USA) seems to do in 2025, especially for grads:

  1. Get very good at algorithm & Data Structure problems.
    • Practice problems involving arrays, strings, linked lists, trees/graphs, hash maps, heaps, etc.
    • Pay attention to complexity: Big-O time and space. Know how to optimize.
    • Use timed coding platforms; simulate the test environment.
  2. Mock interviews and coding practice under constraints.
    • Use platforms or peers to simulate live problems.
    • Practice writing code without too much reliance on IDE autocomplete. (Some interviews or OAs expect you to write code “manually” or with minimal tooling).
  3. Study Amazon’s Leadership Principles (LPs).
    • Amazon has 16+ LPs (Customer Obsession, Ownership, Learn and Be Curious, etc.). These are not just “fluff” – many behavioral questions are derived from them.
    • Prepare several stories from your experience where you demonstrate LPs: failure, impact, trade-offs, etc. Use STAR (Situation, Task, Action, Result).
  4. Practice the Online Assessment (OA) thoroughly.
    • Understand the format: coding questions, work-styles assessment, work simulation. (amazon.jobs)
    • Time management: if you get stuck, move on, then return. Don’t spend forever on one question.
    • Clarity in reading instructions; sometimes assessments penalize for misunderstanding.
  5. Prepare for phone screens / video calls.
    • Be ready to share your screen; code on a whiteboard or online editor.
    • Clarify questions before jumping to solutions. Asking clarifying questions shows you think carefully.
    • Solve smaller toy problems cleanly if asked.
  6. Behavioral preparation.
    • Think of 4-6 stories/examples that show leadership, dealing with ambiguity, teamwork, drive, handling failure/success.
    • Rehearse “Why Amazon?” but in a way that feels authentic. Know something about Amazon (its services, culture, especially recent news or products if possible).
  7. Understand the environment & location.
    • When offered, look carefully at offer letters: base salary, RSU vesting schedule, bonus, relocation, benefits.
    • Calculate cost of living in that location (Seattle, Bay Area, San Jose, etc). Even if salary is high, living costs (housing, tax, etc.) must be considered.
    • For international applicants: understand tax implications, benefits, whether Amazon helps with relocation and visa.

Recent Trends & What Is Changing (2025)

  • Salary inflation & competitive compensation: The compensation bands have increased, especially with high demand in machine learning / cloud / AI infrastructure roles. Entry levels are getting more aggressive offers with more RSUs, especially in expensive areas. (Levels.fyi)
  • Remote / flexible work & location premium: Location still matters—geographic premium is real. Working in an expensive area yields higher base / RSU. If remote is allowed, the policy might reduce or adjust location-based compensation. Be careful to ask.
  • Emphasis on leadership & behavioral traits: Interviewers now often probe more deeply into LPs. It’s not just coding—how you work, communicate, make trade-offs, learn from mistakes is emphasized more.
  • Longer timelines for applicants, especially international: Due to visa processing, degree verification, background checks, etc., international applicants often experience delays in the process.
  • More use of data / work simulation in assessments: Amazon’s OAs for SDE roles are more rigorous now; sometimes include work-style/cognitive tests, simulation of realistic tasks, etc. (amazon.jobs)

Sample Salary Table: SDE I vs SDE II in Key U.S. Locations

Here’s a comparative look at what graduate (new grad) vs slightly more experienced software engineers (1-3 years) might expect in several U.S. tech-center cities in 2025. These are estimates drawn from public data; actual offers may vary.

City / Region SDE I (New Grad, L4) Total Comp Estimate* SDE II (L5, 1‐3 yrs) Total Comp Estimate* Comments / Location Premiums
Seattle, WA ~$165,000-$190,000 ~$250,000-$300,000+ Seattle is Amazon’s HQ region; costs are high but compensation tends to reflect that.
San Francisco Bay Area / Silicon Valley ~$180,000-$210,000 ~$280,000-$330,000+ Very high cost of living; high RSU components.
New York City ~$170,000-$200,000 ~$260,000-$310,000+ Again, location premiums apply. Taxes (state, city) can significantly reduce net take-home.
Austin, TX ~$150,000-$180,000 ~$230,000-$280,000+ Lower cost of living compared to Bay Area / NYC; still gets good compensation.
Remote / Suburban locations May be adjusted lower depending on cost of living policy Same as above, incremental adjustment Always check what Amazon’s policy is for remote / hybrid work in that specific role.

* Total Comp = base salary + estimated bonus + RSUs for year 1 (pro rata vesting). These are ballpark, not hard promises.

Application Strategy: What Gives You an Edge

For an international applicant, stacking the odds in your favor means thinking not just “can I pass the interview?” but “how can I present myself to minimize friction, maximize clarity, and demonstrate fit?”

Here are some strategic choices:

  • Tailor your resume: Highlight projects (especially if they show production code, teamwork, or complexity). Use metrics when possible (“reduced runtime by X%”, “handled N users”, etc.). If you have open source experience, internships, hackathons, or coding competition wins, that helps.
  • Choose the right programming languages: Use ones that are well accepted (Java, C++, Python). If you have a strong preference, make sure you can write code fluently under time constraints in it.
  • Prepare for RSU discussions / understand them: Even if you don’t negotiate much as a grad, understand how RSU vesting works, what is typical for L4, and what your expectations are. Sometimes offers might include RSU + signing bonuses which can be significant.
  • Network & referrals: If possible, get in touch with current Amazonians or alumni; attend virtual info sessions or university recruiting fairs Amazon holds. Sometimes a referral can get your resume more visibility.
  • Plan degree & visa timing carefully: Ensure your degree will be completed by start date; ensure that you have the right documentation; research the necessary steps for endorsing foreign credentials if required. Be ready to show certificates, transcripts, etc.
  • Stay updated on Amazon’s posted Graduate SDE roles and windows: Many postings have application deadlines or are only open during certain recruiting seasons. Don’t wait until the last moment.

Common Pitfalls & How to Avoid Them

  • Under-preparing behaviorally: Many candidates get tripped up by behavioral / LP questions because they think coding is all that matters. But interviewers often shift between technical and behavioral seamlessly. Make sure you have stories prepped.
  • Poor understanding of complexity / performance: Giving a correct solution is good, but if it’s inefficient (e.g. O(n²) when expected O(n log n)) and you don’t address optimizations or trade-offs, that can cost you.
  • Not clarifying the question during interviews: When a problem is poorly defined or you need assumptions, asking is better than assuming wrongly. Interviewers expect clarifying questions.
  • Time mismanagement during the OA or coding rounds: Getting stuck on one problem and losing time on others is a common issue. Best strategy is to keep an eye on time, maybe do easier problems first or partition time.
  • Not aligning behavioral stories to company values: Amazon’s Leadership Principles are many, but frequently cited ones are Customer Obsession, Ownership, Dive Deep, Bias for Action, etc. Use examples that show impact, ownership, curiosity, learning.
  • Visa / documentation surprises: If your degree isn’t yet certified, or transcripts not in expected format, or there are delays in authorization, these things sometimes stall or weaken offers. Always clarify in the offer phase what is required.

Assessment Tips: What to Focus On (Coding + Non-Coding)

To get through Amazon’s assessments and interviews smoothly, here’s a more detailed “prep checklist”:

  • Coding Problem Types to Practice
    • Arrays, Strings, Hash Maps / Sets
    • Trees, Graphs, BFS / DFS, shortest paths, etc.
    • Sorting, Searching, Divide & Conquer
    • Dynamic Programming basics (for some tougher rounds)
    • Recursion vs iteration trade-offs
    • Edge cases, error cases, input validation
  • Algorithmic Complexity
    • Always discuss and think about time (how fast) and space (how much memory) complexity.
    • If your initial solution is brute-force, think of improvements.
  • Clean Code Practices
    • Good naming, structuring code, comments only if needed (avoid over-commenting), readable style.
    • If test cases are provided (or interviewer asks), consider them; sometimes coding in an interview environment means whiteboard or shared editor.
  • System Design (if applicable, even for grads in some teams)
    • Might be light, but knowing basic design patterns, trade-offs, scalability topics helps.
    • E.g. designing a simple REST service, scaling reads/writes, caching, dealing with failure.
  • Behavioral / Leadership Principles
    • Prepare stories for: times when you took ownership, made a mistake & what you learned, dealt with ambiguity, prioritized conflicting tasks, led or influenced peers, delivered under deadline.
    • Use STAR (Situation, Task, Action, Result) structure. Be specific (numbers / impact) if possible.
  • “Why Amazon?”
    • Have more than generic reasons. If possible, tie to specific products, culture features, or recent initiatives of Amazon you admire and how your goals align.
  • Mock Rounds / Feedback
    • Simulate full loops (coding + behavioral) with friends or mentors. Get feedback.
    • After coding practice, reflect: what mistakes did you make? What would you do differently?
  • Technical Environment Preparedness
    • For the OA, ensure your hardware / internet connection is stable. Make sure the device meets required specs.
    • Practice typing code under constraints; sometimes the test interface is simpler than your IDE—no syntax suggestions, etc.

Visa / Immigration / International Specifics

Since this is a big part for non-U.S. applicants, here are what you should research / clarify early:

  • Visa Sponsorship: Does Amazon sponsor H-1B, or use OPT/CPT if you’re a student? What documentation they will require?
  • Start date vs Degree Completion: Amazon often requires that the candidate has completed (or will complete) their degree before starting. If your graduation date is too late, you may run into issues.
  • Credential Evaluation: If your educational credentials are from a non-U.S. institution, be ready to supply transcripts, translations, evaluations if needed.
  • Relocation / Immigration Assistance: Some offers include support for relocating, visa application, etc. Sometimes Amazon or its local vendor / affiliate helps, but sometimes less so. Ask in the offer stage.
  • Taxes, Cost of Living & Compensation Net: Even though gross compensation might look large, there are U.S. federal & state incomes taxes, maybe city taxes, cost of housing, health insurance. Also, RSUs are taxed. Make sure you understand net salary (after deductions).

Putting It All Together: A Sample Timeline for an International Applicant

Here’s a hypothetical timeline / preparation plan so that you can map actions to time.

Time Before Application Window Starts What to Do
~6 months prior Brush up on data structures & algorithms; build or polish projects; ensure your resume reflects relevant work/internships. If still finishing degree, confirm you’ll graduate in time.
~3 months prior Begin timed practice of OA-type questions; practice mock interviews; prepare behavioral stories; network with Amazon or alumni; review Amazon’s LPs.
When applications open Apply early; tailor your resume; ensure all documents (degree, transcripts) are ready. If possible, get a referral.
After applying & during OA stage Take OA in a distraction-free place; manage time; if get phone screen, prep for both coding & behavioral. Always clarify questions.
Interview loop stage Be polished: clean code, vocal explanation, ask clarifying questions, show curiosity; rest well before interview days.
When you get offer Carefully check salary, RSU vesting schedule, benefit package, visa/relocation support; maybe negotiate if you have leverage (rare for straight grads, but sometimes possible).

Conclusion

Landing a graduate/new grad SDE role at Amazon (USA) in 2025 is a challenging but highly rewarding goal—especially for international applicants. The compensation is strong, with entry-level total compensation for L4 roles often ranging from roughly $165,000 to $190,000 or more depending on location. What matters just as much as technical chops are behavioral fit, clear communication, project evidence, and being ready for visa / documentation requirements.