As a Software Engineer at Toast, you are at the heart of a platform that powers the restaurant industry. You are not just writing code; you are building the critical infrastructure that allows restaurants to operate, process payments, manage inventory, and delight their guests. Your work directly impacts the daily lives of restaurant owners, staff, and patrons, requiring a balance of technical rigor and a deep empathy for the user experience. The role involves working across a modern, high-scale tech stack, often involving Java, Kotlin, React, and Go, depending on your specific team. Whether you are working on backend services that handle high-concurrency transaction processing or frontend interfaces that must be intuitive in a fast-paced kitchen environment, you are expected to solve complex, real-world problems. Toast values engineers who can navigate ambiguity, communicate effectively, and contribute to a collaborative, product-focused engineering culture.
Recruiter Screen
reportedInitial contact with the recruiter to assess candidate fit and discuss the role.
What to demonstrate
- Initial contact with the recruiter to assess candidate fit and discuss the role
- Depth in Array processing (map, filter, reduce)
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 Coding Assessment
reportedCandidates complete a technical coding assessment to evaluate their programming skills.
What to demonstrate
- Candidates complete a technical coding assessment to evaluate their programming skills
- Depth in Array processing (map, filter, reduce)
How to prepare
- Answer aloud and timed: How would you find the optimal buy-and-sell day for a stock to maximize profit?
- Answer aloud and timed: Can you walk me through your approach to filtering and mapping nested JSON objects?
Deep-Dive Panel Interviews
reportedA series of in-depth panel interviews focusing on technical and behavioral aspects.
What to demonstrate
- A series of in-depth panel interviews focusing on technical and behavioral aspects
- Depth in Array processing (map, filter, reduce)
How to prepare
- Answer aloud and timed: How would you implement a specific component or feature using React?
- Answer aloud and timed: Can you describe a time you had to deal with a challenging technical disagreement with a peer?
1 candidate reports. Individual accounts describe a particular role and hiring cycle.
Toast Software Engineer Interview Experience — Coding Screen, Four-Round Virtual Onsite, Rejected
First was a coding round. It didn't seem too hard, basically one map and one loop, and it was a question I'd seen on the forum. After that came the long, stinky virtual onsite. System design: this was also on the forum. It's basically designing a restaurant seat reservation system. I'd suggest looking at Alex Xu's book, which has something similar, and then summarizing it yourself. This round was…
Read full experiencePracHub editorial advice for the preparation topics above.
Prioritize clarity
When explaining your thought process, use simple, direct language. Avoid over-complicating your explanations.
Prepare your stories
Use the STAR method (Situation, Task, Action, Result) for all behavioral questions to keep your answers structured and impactful.
Research the product
Familiarize yourself with how Toast works in a restaurant setting. Understanding the "why" behind the software will give you a significant edge.
Ask questions
Use the time at the end of the interview to ask about engineering culture, team challenges, or the roadmap. It shows genuine interest and engagement.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
How would you implement a palindrome validation function with specific character constraints?
How would you implement a palindrome validation function with specific character constraints?
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?
Can you explain the time and space complexity of your solution for this string manipulation task?
Can you explain the time and space complexity of your solution for this string manipulation task?
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?
How would you find the optimal buy-and-sell day for a stock to maximize profit?
How would you find the optimal buy-and-sell day for a stock to maximize profit?
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?
Can you walk me through your approach to filtering and mapping nested JSON objects?
Can you walk me through your approach to filtering and mapping nested JSON objects?
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?
How would you implement a specific component or feature using React?
How would you implement a specific component or feature using React?
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?
Stop tag and share joins from fanning out a page
resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.
Approach
- Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
- Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
- Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
- Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.
Follow-up
- The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
- A resource can be shared with the same user twice under different permissions. Does your count change, and should it?
Hold a per-tenant active cap against concurrent creates
A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.
Approach
- Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
- Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
- Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
- State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.
Follow-up
- A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
- The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?
How would you design a system to handle eventual consistency in a distributed environment?
How would you design a system to handle eventual consistency in a distributed environment?
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?
What are the trade-offs between different database choices for a high-traffic ordering system?
What are the trade-offs between different database choices for a high-traffic ordering system?
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?
How do you ensure your API design is scalable and maintainable?
How do you ensure your API design is scalable and maintainable?
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?
How would you approach requirements gathering for a new service?
How would you approach requirements gathering for a new 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?
One log partition stops advancing while the others drain
Search results for a subset of tenants are hours stale; the rest are current. The projection consumer reports lag of zero on 15 of 16 partitions and 400,000 on one. Its error rate is flat and its CPU is idle. outbox_event has no pending rows older than a second, so the relay has published everything it holds. Identify the mechanism, give the ordered checks, and state what you do in the first ten minutes versus what you change permanently.
Approach
- Read the lag distribution first. A slow consumer lags everywhere; zero on fifteen partitions and 400,000 on one is not throughput. Idle CPU on the stuck partition means the consumer is not advancing its offset at all, which points at one message it cannot get past rather than at a rate problem.
- Exonerate the producer before touching the consumer. No pending outbox rows older than a second means the relay published, so the event exists in the log. This separates never sent from sent and never applied, which are different code paths and usually different owners.
- Read the message at the stuck offset and the handler's log lines for its event_id. A flat error rate with no progress has two explanations and you must distinguish them: the handler is throwing and the retry loop is swallowing it, or the handler is blocking on something and never returning. Idle CPU with no error lines favours the second.
- Mitigate before diagnosing further. Move the offending event to a dead-letter store and commit the offset past it. Adding consumers does nothing here, because a partition is consumed by exactly one member of the group, and the blast radius is every aggregate hashed to that partition, not only the aggregate that produced the bad event.
Follow-up
- The dead-lettered event carried aggregate_version 7 and the projection had applied 6. What must the replay do differently if 8 and 9 landed in the meantime?
- How do you show staleness to the user while the partition is behind, given the API already returns the projection's watermark?
Built from the rounds and topics Toast candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Toast loop
- Write out the reported sequence: Recruiter Screen, Technical Coding Assessment, Deep-Dive Panel Interviews.
- 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 3 reported rounds, with the weakest marked.
02Work Array processing (map, filter, reduce)
- Spend the session on Array processing (map, filter, reduce), which Toast candidates report being tested on.
- Write one worked example in Array processing (map, filter, reduce) and time yourself on it.
Deliverable: One timed worked example in Array processing (map, filter, reduce).
03Work Golang (Go)
- Spend the session on Golang (Go), which Toast candidates report being tested on.
- Write one worked example in Golang (Go) and time yourself on it.
Deliverable: One timed worked example in Golang (Go).
04Work Concurrency concepts (multithreading vs goroutines)
- Spend the session on Concurrency concepts (multithreading vs goroutines), which Toast candidates report being tested on.
- Write one worked example in Concurrency concepts (multithreading vs goroutines) and time yourself on it.
Deliverable: One timed worked example in Concurrency concepts (multithreading vs goroutines).
05Answer out loud: Coding and Algorithms
- Answer aloud, timed: How would you implement a palindrome validation function with specific character constraints?
- Answer aloud, timed: Can you explain the time and space complexity of your solution for this string manipulation task?
Deliverable: Spoken answers to 2 reported Coding and Algorithms question(s), under time.
06Answer out loud: Behavioral and Cultural Fit
- Answer aloud, timed: Can you describe a time you had to deal with a challenging technical disagreement with a peer?
- Answer aloud, timed: Why are you interested in the restaurant technology space?
Deliverable: Spoken answers to 2 reported Behavioral and Cultural Fit question(s), under time.
07Answer out loud: System Design and Architecture
- Answer aloud, timed: How would you design a system to handle eventual consistency in a distributed environment?
- Answer aloud, timed: What are the trade-offs between different database choices for a high-traffic ordering system?
Deliverable: Spoken answers to 2 reported System Design and Architecture 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.
Can you describe a time you had to deal with a challenging technical disagreement with a peer?
Can you describe a time you had to deal with a challenging technical disagreement with a peer?
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?
Why are you interested in the restaurant technology space?
Why are you interested in the restaurant technology space?
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?
Tell me about a time you had to learn a new technology quickly to complete a project.
Tell me about a time you had to learn a new technology quickly to complete a project.
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 feedback during a code review?
How do you handle feedback during a code review?
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 project where you had to balance technical debt with the need for a quick feature delivery.
Describe a project where you had to balance technical debt with the need for a quick feature delivery.
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
Can you describe a time you had to deal with a challenging technical disagreement with a peer?
- 02
Why are you interested in the restaurant technology space?
- 03
Tell me about a time you had to learn a new technology quickly to complete a project.
- 04
How do you handle feedback during a code review?
How long does the process take?
The process typically takes 3 to 5 weeks from the initial recruiter screen to the final decision. It is designed to be swift, but coordination across teams can sometimes extend the timeline.
Toast Software Engineer candidate reports ↗Are the technical questions always LeetCode-style?
Not necessarily. While you will encounter coding challenges, many are designed to be collaborative discussions or practical problems related to Toast’s actual engineering challenges.
Toast Software Engineer candidate reports ↗What is the best way to stand out?
Be collaborative. The most successful candidates treat the interview like a pair-programming session. Ask clarifying questions, discuss trade-offs, and show that you are thinking about the user and the business, not just the code.
Toast Software Engineer candidate reports ↗How should I handle a question I don't know the answer to?
Be transparent. If you don't know a specific technology or concept, explain how you would go about finding the answer or what your intuition tells you based on similar problems you have solved.
Toast Software Engineer candidate reports ↗What topics does Toast test in interviews?
Toast interviews most often cover Behavioral Interviewing, Communication Skills, Stakeholder Management, Cross-functional Collaboration, and Hiring Manager Interviewing. The exact emphasis depends on the specific role you apply for.
Toast Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
Official role evidence, timestamped platform data and clearly labeled preparation advice.
- 01Toast Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
candidate · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
platform · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
platform · Accessed 2026-09-22
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