As a Software Engineer at Kake, you are a foundational contributor to the technical infrastructure that powers our partner-facing solutions. You will not just be writing code; you will be solving complex, real-world problems that directly impact how our clients operate and scale. This role demands a high level of autonomy, technical craftsmanship, and the ability to bridge the gap between abstract business requirements and robust, scalable software. The work environment at Kake is dynamic and often involves high-stakes collaboration with external clients. You will frequently find yourself working on cross-functional projects where your ability to communicate technical trade-offs to non-technical stakeholders is as important as your ability to write clean, maintainable code. This position is ideal for engineers who thrive in fast-paced environments and are motivated by the challenge of delivering high-quality, impactful software in a collaborative, partner-centric ecosystem.
Recruiter Screen
reportedInitial screening call with a recruiter to assess fit for the role.
What to demonstrate
- Initial screening call with a recruiter to assess fit for the role
- Depth in System Design Interview
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
reportedMultiple technical assessments to evaluate your technical depth.
What to demonstrate
- Multiple technical assessments to evaluate your technical depth
- Depth in System Design Interview
How to prepare
- Answer aloud and timed: What are the trade-offs between the frameworks you have used in your recent projects?
- Answer aloud and timed: How do you ensure code quality and maintainability in a fast-paced environment?
Behavioral Interviews
reportedInterviews with project leads or Engineering Managers to assess alignment.
What to demonstrate
- Interviews with project leads or Engineering Managers to assess alignment
- Depth in System Design Interview
How to prepare
- Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
- Re-read the description of the behavioral interviews above and write down what you would ask to confirm before it.
PracHub editorial advice for the preparation topics above.
Own your narrative
When discussing past projects, clearly state your specific contribution. Use the STAR method (Situation, Task, Action, Result) to keep your answers structured.
Ask meaningful questions
Use the time at the end of the interview to ask about the team’s current technical challenges or how they measure success. This demonstrates genuine interest.
Stay human
Remember that your interviewers are your potential future colleagues. A professional yet authentic demeanor goes a long way.
Prepare for ambiguity
Real-world engineering rarely has a single "correct" answer. When given a problem, clarify your assumptions early.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Identify the heaviest tenants in a five-minute window under memory pressure
The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.
Approach
- Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
- Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
- State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
- Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.
Follow-up
- The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
- Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?
Track a rolling failure rate per destination for circuit decisions
The egress service delivers about 1,500 webhooks per second across roughly 40,000 destinations, each call bounded by a 10 second timeout. Maintain, per destination, the failure rate over the trailing 60 seconds so a caller can ask before dispatch whether the circuit should open. Attempts arrive as (destination_id, finished_at_ms, outcome). Requirement: amortised O(1) per attempt, with total memory bounded by the destination count rather than by traffic. Give the structure, its exact memory, and the rule that stops a destination with three attempts from opening a circuit.
Approach
- Name the exact-deque version and then reject it as the default. Holding timestamps and advancing a tail pointer past anything older than now minus 60 seconds is a correct two-pointer window at amortised O(1) per attempt, but its memory tracks in-window traffic, so one destination in a retry storm holds hundreds of thousands of entries while thousands of quiet destinations hold none.
- Use a ring of 60 one-second buckets per destination, each bucket a pair of counters for attempts and failures. On an attempt, advance the ring by the elapsed whole seconds, zeroing at most min(elapsed, 60) buckets, then increment the head. That is amortised O(1) with a fixed footprint per destination.
- State the footprint: 60 buckets times two 4-byte counters is 480 bytes of payload per destination, so 40,000 destinations is roughly 20 to 25 MB with per-entry overhead, bounded by the catalogue rather than by the rate. The cost is granularity, since the oldest bucket ages out in whole seconds, which is far tighter than the decision needs.
- Require a minimum sample before the circuit may open. A destination with three attempts and three failures reads as 100 percent and is not evidence; a floor of roughly 20 attempts in the window makes the ratio meaningful, and below that floor use a run of consecutive failures as the trigger instead.
Follow-up
- The fleet is 30 instances and each sees roughly a thirtieth of a destination's traffic. Where does the rate actually live, and what does a per-instance answer get wrong?
- A destination answers in 9.5 seconds and succeeds. It is not failing but it is consuming your per-destination concurrency. What signal should open the circuit here?
Diff a projection against the primary without per-row point reads
The listing projection has drifted and some rows show a stale version. The primary holds 40,000,000 resource rows across 12,000 tenants while serving 1,200 writes and 14,000 reads per second. The obvious repair, reading each resource row and comparing its version against the projection, is correct and would eventually finish. Explain precisely why it is unacceptable here, then give a diff that finds the differing rows, state its complexity, and make it safe to run against a live primary. Replication lag is usually under 100 ms and is not bounded.
Approach
- Quantify the naive cost rather than calling it slow: 40,000,000 point reads at even 0.5 ms each is over five hours serialised, and the only lever is concurrency, which is exactly what you cannot spend. The primary's pool is sized for the write path, and 40,000,000 random reads evict the buffer cache that sustains the 85 percent cache hit rate, so the audit degrades the system it is auditing.
- Replace random access with one ordered pass per side. Both sides can be read in (tenant_id, resource_id) order, which is a sequential scan on each and a merge join in O(n) time and O(1) memory. For a dense diff that is the whole answer, and it reads the primary once instead of 40,000,000 times.
- For the expected sparse case, compare range hashes instead of rows: partition the key space, compute per range an order-independent aggregate over hash(resource_id, version), compare aggregates, and descend only into ranges that differ. With d differing rows and branching factor B, at most d ranges mismatch per level, so the drill-down examines O(d log_B(n/d)) ranges and reads full rows only in mismatching leaves.
- Aggregate with a sum modulo 2^64 or a multiset hash, never XOR. XOR is order-independent but self-cancelling, so two rows wrong in the same way, or a row duplicated on one side, leave the range aggregate matching and the range is declared clean.
Follow-up
- The diff reports 900 stale rows. How do you decide between patching those rows and rebuilding the projection from resource_revision?
- Same job, but the projection lives in a search index that cannot be scanned in key order. What changes?
Denormalise tenant onto revisions and backfill it live
resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.
Approach
- Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
- Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
- Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
- Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.
Follow-up
- The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
- How do you verify the backfill actually finished, given rows are still being inserted while it runs?
Replace offset paging on the resource feed with keyset
resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.
Approach
- Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
- Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
- Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
- Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.
Follow-up
- The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
- Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?
Can you walk me through the architecture of the most complex system you have built?
Can you walk me through the architecture of the most complex system you have built?
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 the frameworks you have used in your recent projects?
What are the trade-offs between the frameworks you have used in your recent projects?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How do you ensure code quality and maintainability in a fast-paced environment?
How do you ensure code quality and maintainability in a fast-paced environment?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Explain the concept of [specific technical concept] and how you have applied it to solve a bottleneck.
Explain the concept of [specific technical concept] and how you have applied it to solve a bottleneck.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How would you design a system to handle [specific high-traffic scenario]?
How would you design a system to handle [specific high-traffic scenario]?
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 factors do you consider when choosing between a relational and a non-relational database for a new projec
What factors do you consider when choosing between a relational and a non-relational database for a new project?
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?
If you had to redesign our current process for [specific feature], where would you start?
If you had to redesign our current process for [specific feature], where would you start?
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 balance speed of delivery with long-term technical debt?
How do you balance speed of delivery with long-term technical debt?
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 approach debugging a production issue in a distributed system?
How do you approach debugging a production issue in a distributed system?
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Built from the rounds and topics Kake candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Kake loop
- Write out the reported sequence: Recruiter Screen, Technical Assessments, Behavioral 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 System Design Interview
- Spend the session on System Design Interview, which Kake candidates report being tested on.
- Write one worked example in System Design Interview and time yourself on it.
Deliverable: One timed worked example in System Design Interview.
03Work Live Coding (Technical Interview)
- Spend the session on Live Coding (Technical Interview), which Kake candidates report being tested on.
- Write one worked example in Live Coding (Technical Interview) and time yourself on it.
Deliverable: One timed worked example in Live Coding (Technical Interview).
04Work Scalability/Architecture Reasoning (Implied by System Design)
- Spend the session on Scalability/Architecture Reasoning (Implied by System Design), which Kake candidates report being tested on.
- Write one worked example in Scalability/Architecture Reasoning (Implied by System Design) and time yourself on it.
Deliverable: One timed worked example in Scalability/Architecture Reasoning (Implied by System Design).
05Answer out loud: Technical Foundations & Domain Expertise
- Answer aloud, timed: Can you walk me through the architecture of the most complex system you have built?
- Answer aloud, timed: How do you handle state management in large-scale applications?
Deliverable: Spoken answers to 2 reported Technical Foundations & Domain Expertise question(s), under time.
06Answer out loud: System Design & Problem Solving
- Answer aloud, timed: How would you design a system to handle [specific high-traffic scenario]?
- Answer aloud, timed: What factors do you consider when choosing between a relational and a non-relational database for a new project?
Deliverable: Spoken answers to 2 reported System Design & Problem Solving question(s), under time.
07Answer out loud: Behavioral & Cultural Alignment
- Answer aloud, timed: Tell me about a time you had a technical disagreement with a teammate or client. How was it resolved?
- Answer aloud, timed: How do you handle feedback from a client who may not have a technical background?
Deliverable: Spoken answers to 2 reported Behavioral & Cultural Alignment 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.
How do you handle state management in large-scale applications?
How do you handle state management in large-scale applications?
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 a technical disagreement with a teammate or client. How was it resolved?
Tell me about a time you had a technical disagreement with a teammate or client. How was it resolved?
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 from a client who may not have a technical background?
How do you handle feedback from a client who may not have a technical background?
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 situation where you had to learn a new technology quickly to complete a project.
Describe a situation where 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?
What do you look for in a team environment to be most productive?
What do you look for in a team environment to be most productive?
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 went above and beyond for a project or client.
Tell me about a time you went above and beyond for a project or client.
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
How do you handle state management in large-scale applications?
- 02
Tell me about a time you had a technical disagreement with a teammate or client. How was it resolved?
- 03
How do you handle feedback from a client who may not have a technical background?
- 04
Describe a situation where you had to learn a new technology quickly to complete a project.
How long does the process usually take?
While it varies, the process typically spans 2 to 4 weeks. We aim to keep communication lines open, but please reach out to your recruiter if you encounter a silence longer than one week.
Kake Software Engineer candidate reports ↗Are all technical interviews live coding?
Not necessarily. Some rounds are deep-dive discussions on past projects or system design scenarios. Be prepared for both styles.
Kake Software Engineer candidate reports ↗What if I don't know the answer to a technical question?
Be honest. It is better to talk through your thought process and how you would find the answer than to guess. We value transparency and the ability to learn.
Kake Software Engineer candidate reports ↗Is the culture at Kake remote-friendly?
Kake operates in a highly flexible, global, or regional remote-first context. Expect to work with distributed teams and practice asynchronous communication.
Kake Software Engineer candidate reports ↗How many rounds does Kake have for a Software Engineer interview?
Kake’s Software Engineer interview flow starts with a recruiter screen, then moves into multiple technical assessments, and finishes with behavioral interviews with project leads or Engineering Managers. The guide also notes the process can involve multiple teams and that the timeline may fluctuate based on client needs.
Kake Software Engineer candidate reports ↗What does Kake test for Software Engineer interviews, and what topics should I prioritize?
Expect evaluation across technical depth, live problem solving, system design, and behavioral fit. The listed top topics include system design, live coding (technical interview), state management at scale, design for high-traffic scenarios, behavioral interviewing, and culture fit.
Kake Software Engineer candidate reports ↗How should I prepare for the technical assessments at Kake for Software Engineer roles?
Be ready to explain your architecture and your reasoning, not just produce working code. The guide emphasizes structured problem solving, breaking down ambiguous problems, and articulating assumptions before diving into implementation, and it warns that some technical rounds may be conversational while others can involve whiteboard or live-coding sessions.
Kake Software Engineer candidate reports ↗What kinds of behavioral questions does Kake ask a Software Engineer?
Behavioral interviews focus on how you align with team expectations and handle client facing collaboration. The process includes interviews with project leads or Engineering Managers, and the guide highlights themes like technical disagreement resolution and handling feedback from clients who may not have a technical background.
Kake Software Engineer candidate reports ↗What compensation range does Kake offer for a Software Engineer, and does it vary?
The provided data does not include any compensation numbers for Kake Software Engineer roles.
Kake 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.
- 01Kake 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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