As a Software Engineer at Amazon Lab126, you are at the heart of innovation for Amazon’s consumer electronics division. Lab126 is the research and development arm responsible for iconic hardware products including the Kindle, Fire TV, Echo, and other cutting-edge devices. This role is not just about writing code; it is about building the software systems that power the interface between users and physical technology at a massive, global scale. You will work on complex, cross-functional challenges that span low-level firmware, operating systems, cloud-integrated applications, and user-facing features. The work is characterized by high technical rigor, a focus on performance, and the drive to solve problems in resource-constrained environments. Success in this role requires you to be a versatile engineer who can navigate ambiguity, design scalable architectures, and maintain a relentless focus on the end-user experience. This position offers the unique opportunity to see your software run on millions of devices worldwide. You will collaborate closely with hardware engineers, product managers, and other software teams to iterate on products that define how people consume media, interact with smart homes, and access information. If you enjoy the intersection of hardware and software and thrive in an environment that demands both technical depth and creative problem-solving, this is a role where you can have significant, tangible impact.
Recruiter Screen
reportedInitial screening conducted by a recruiter to assess candidate fit for the role.
What to demonstrate
- Initial screening conducted by a recruiter to assess candidate fit for the role
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Be able to walk your CV end to end in two minutes, and say why this company specifically.
- Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.
Technical Assessments
reportedA series of technical evaluations to test coding and problem-solving skills.
What to demonstrate
- A series of technical evaluations to test coding and problem-solving skills
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Answer aloud and timed: Write an algorithm to solve classic problems like merging sorted arrays, reversing a linked list, or tree traversals.
- Answer aloud and timed: Explain the time and space complexity of your solutions and discuss trade-offs in your approach.
Interview Loop
reportedA series of four to six individual interview sessions covering technical coding, system design, and behavioral evaluations.
What to demonstrate
- A series of four to six individual interview sessions covering technical coding, system design, and behavioral evaluations
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Answer aloud and timed: Perform bug-fixing on provided code snippets during online assessments.
- Answer aloud and timed: Provide a high-level overview of how you would design a scalable system for a specific service.
Bar Raiser Interview
reportedOne interview session conducted by a Bar Raiser to ensure high hiring standards and cultural fit.
What to demonstrate
- One interview session conducted by a Bar Raiser to ensure high hiring standards and cultural fit
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Answer aloud and timed: Discuss the trade-offs involved in choosing specific data structures for a given task.
- Answer aloud and timed: Explain your approach to object-oriented design and how you handle concurrency or threading issues.
PracHub editorial advice for the preparation topics above.
Talk through your code
Interviewers want to see how you think. Even if you are stuck, communicate your thought process clearly.
Know your resume
Be prepared to discuss every technical decision you made on your past projects in detail.
Prepare for ambiguity
Some interviewers may intentionally provide vague requirements. Ask clarifying questions to narrow the scope before you start designing or coding.
Practice the STAR method
For every behavioral question, ensure your answer follows the Situation, Task, Action, and Result structure to keep your response concise and impactful.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Implement a function to find the shortest path between two nodes in a tree or graph.
Implement a function to find the shortest path between two nodes in a tree or graph.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Given an array and a query, count how many elements are less than a specific value.
Given an array and a query, count how many elements are less than a specific value.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Write an algorithm to solve classic problems like merging sorted arrays, reversing a linked list, or tree trav
Write an algorithm to solve classic problems like merging sorted arrays, reversing a linked list, or tree traversals.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Explain the time and space complexity of your solutions and discuss trade-offs in your approach.
Explain the time and space complexity of your solutions and discuss trade-offs in your approach.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Perform bug-fixing on provided code snippets during online assessments.
Perform bug-fixing on provided code snippets during online assessments.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Explain your approach to object-oriented design and how you handle concurrency or threading issues.
Explain your approach to object-oriented design and how you handle concurrency or threading issues.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Keep soft-deleted accounts from blocking re-registration
app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.
Approach
- Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
- Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
- For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
- State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.
Follow-up
- A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
- How do you honour an erasure request while resource_revision.actor_user_id still references this table?
Find version gaps and relay lag with window functions
outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.
Approach
- Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
- Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
- Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
- Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.
Follow-up
- Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
- Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?
Provide a high-level overview of how you would design a scalable system for a specific service.
Provide a high-level overview of how you would design a scalable system for a specific service.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Discuss the trade-offs involved in choosing specific data structures for a given task.
Discuss the trade-offs involved in choosing specific data structures for a given task.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Describe how you would integrate software with hardware sensors or manage data processing in real-time.
Describe how you would integrate software with hardware sensors or manage data processing in real-time.
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
p99 jumped on one listing filter while p50 stayed flat
After a release that added an owner_user_id filter to the resource listing, p99 rose from 90 ms to 1.9 s while p50 stayed at 40 ms. Traffic and row counts are unchanged. resource carries the index (tenant_id, status, updated_at DESC, resource_id DESC). The new query filters tenant_id and owner_user_id, orders by updated_at DESC, resource_id DESC, and takes 20 rows. On PostgreSQL, explain the shape of the regression, prove it from a query plan, and give the index you would add.
Approach
- Start from the shape. A flat p50 with a moved p99 means a subset of requests changed cost, not all of them, so the first job is naming the subset. Bucket the endpoint's latency by the tenant's row count; the natural hypothesis is that large tenants are a small share of requests and all of the tail.
- Get the plan for the new query on a large tenant with EXPLAIN (ANALYZE, BUFFERS). Expect an index scan over the tenant's range, a filter discarding most of it, then a Sort feeding the Limit, possibly reporting Sort Method: external merge Disk. Read actual rows on the scan node, not estimated.
- Explain why the existing index cannot serve it. A composite B-tree is seekable only as a left prefix, and with no equality predicate on status the scan cannot treat updated_at as an ordering, because rows in the tenant's range are ordered by status first. Everything matching must be read and sorted before LIMIT 20 can apply, so a tenant with 400,000 rows pays 400,000 rows to return 20.
- Add (tenant_id, owner_user_id, updated_at DESC, resource_id DESC). Equality on the first two columns leaves the index ordered by updated_at within that pair, so the plan becomes an index scan that stops after 20 rows with no Sort node. PostgreSQL can scan a B-tree backwards, so the DESC markers matter only if the two sort columns ever disagree in direction; keeping them explicit documents the order the keyset cursor depends on.
Follow-up
- The endpoint paginates with OFFSET. What does page 500 cost with your index, and what does the keyset version cost?
- How would you have caught this before release, given that a 10,000-row seed database produces the same plan shape at an unnoticeable cost?
Built from the rounds and topics Amazon Lab126 candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Amazon Lab126 loop
- Write out the reported sequence: Recruiter Screen, Technical Assessments, Interview Loop, Bar Raiser Interview.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 4 reported rounds, with the weakest marked.
02Work Data Structures & Algorithms (DSA)
- Spend the session on Data Structures & Algorithms (DSA), which Amazon Lab126 candidates report being tested on.
- Write one worked example in Data Structures & Algorithms (DSA) and time yourself on it.
Deliverable: One timed worked example in Data Structures & Algorithms (DSA).
03Work Problem Solving
- Spend the session on Problem Solving, which Amazon Lab126 candidates report being tested on.
- Write one worked example in Problem Solving and time yourself on it.
Deliverable: One timed worked example in Problem Solving.
04Work System Design
- Spend the session on System Design, which Amazon Lab126 candidates report being tested on.
- Write one worked example in System Design and time yourself on it.
Deliverable: One timed worked example in System Design.
05Answer out loud: Coding and Algorithms
- Answer aloud, timed: Implement a function to find the shortest path between two nodes in a tree or graph.
- Answer aloud, timed: Given an array and a query, count how many elements are less than a specific value.
Deliverable: Spoken answers to 2 reported Coding and Algorithms question(s), under time.
06Answer out loud: System Design and Architecture
- Answer aloud, timed: Provide a high-level overview of how you would design a scalable system for a specific service.
- Answer aloud, timed: Discuss the trade-offs involved in choosing specific data structures for a given task.
Deliverable: Spoken answers to 2 reported System Design and Architecture question(s), under time.
07Answer out loud: Behavioral and Leadership
- Answer aloud, timed: Tell me about a time you made a decision that was difficult in the moment but benefited the company long-term.
- Answer aloud, timed: Describe a challenging project you worked on and how you handled conflict within your team.
Deliverable: Spoken answers to 2 reported Behavioral and Leadership question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Tell me about a time you made a decision that was difficult in the moment but benefited the company long-term.
Tell me about a time you made a decision that was difficult in the moment but benefited the company long-term.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Describe a challenging project you worked on and how you handled conflict within your team.
Describe a challenging project you worked on and how you handled conflict within your team.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
How do you handle situations where a manager asks you to do something you believe is not in the best interest
How do you handle situations where a manager asks you to do something you believe is not in the best interest of the product?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Give an example of how you have demonstrated "ownership" or "bias for action" in a previous role.
Give an example of how you have demonstrated "ownership" or "bias for action" in a previous role.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Explain a time you had to learn a new technology or domain quickly to solve a problem.
Explain a time you had to learn a new technology or domain quickly to solve a problem.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
- 01
Tell me about a time you made a decision that was difficult in the moment but benefited the company long-term.
- 02
Describe a challenging project you worked on and how you handled conflict within your team.
- 03
How do you handle situations where a manager asks you to do something you believe is not in the best interest of the product?
- 04
Give an example of how you have demonstrated "ownership" or "bias for action" in a previous role.
How long should I prepare for the interview?
Most successful candidates dedicate 4–8 weeks to preparation, depending on their current familiarity with algorithm problems and their experience with behavioral interview structures.
Amazon Lab126 Software Engineer candidate reports ↗What is the "Bar Raiser" role?
A Bar Raiser is an experienced interviewer from a different team. They are there to ensure that every new hire is better than 50% of the current team in that role, maintaining a high standard of quality across the company.
Amazon Lab126 Software Engineer candidate reports ↗How much time is spent on behavioral questions vs. technical questions?
Expect roughly 30–50% of each interview to be dedicated to Leadership Principles or behavioral questions. Do not underestimate this; it is a major part of the evaluation.
Amazon Lab126 Software Engineer candidate reports ↗Can I get feedback if I am not selected?
Due to company policy, Amazon typically does not provide specific feedback on interview performance.
Amazon Lab126 Software Engineer candidate reports ↗What topics does Amazon Lab126 test in interviews?
Amazon Lab126 interviews most often cover Behavioral Interviewing, Problem Solving, Stakeholder Communication, Leadership Principles Alignment, and Data Structures & Algorithms (DSA). The exact emphasis depends on the specific role you apply for.
Amazon Lab126 Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Amazon Lab126 Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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