Kis Solutions Software Engineer Interview Guide

The 60-second brief

A Software Engineer at Kis Solutions is a pivotal contributor to our technical infrastructure and client-facing solutions. You are not just writing code; you are solving real-world problems through logic, precision, and effective communication. Your work directly impacts the stability and functionality of the systems our clients rely on, requiring a balance of deep technical expertise and the ability to collaborate across teams. This role is designed for engineers who thrive in environments where technical rigor meets practical application. Whether you are addressing complex algorithmic challenges or integrating new technologies to meet specific client needs, your contributions are central to our operational success. We look for individuals who are intellectually curious, comfortable with ambiguity, and committed to delivering high-quality, maintainable code.

This guide is scoped to a Software Engineer candidate at Kis Solutions.

Focus areas

• Technical Interviewing
• Programming Problem Solving
• Algorithmic Thinking

The Kis Solutions interview process

Kis Solutions candidates report 5 rounds over 4-6 weeks. The stages below are what candidates describe, not a published process.

Initial Assessment

Assessment of your background and language skills.

What to demonstrate

• Assessment of your background and language skills
• Depth in Technical Interviewing

How to prepare

• Answer aloud and timed: Can you walk me through your approach to solving this algorithmic challenge?
• Answer aloud and timed: How would you optimize this function for better performance or lower memory usage?

Technical Evaluation

Deep dive into your technical capabilities with hands-on challenges.

What to demonstrate

• Deep dive into your technical capabilities with hands-on challenges
• Depth in Technical Interviewing

How to prepare

• Answer aloud and timed: Please explain your choice of data structure for this specific problem.
• Answer aloud and timed: How do you handle edge cases when writing code for production?

Engagement with Recruiters

Interaction with both recruiters and technical managers.

What to demonstrate

• Interaction with both recruiters and technical managers
• Depth in Technical Interviewing

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.

Skill Demonstration

Demonstrate your skills across different technologies.

What to demonstrate

• Demonstrate your skills across different technologies
• Depth in Technical Interviewing

How to prepare

• Answer aloud and timed: Why are you interested in joining the team at Kis Solutions?
• Answer aloud and timed: How do you handle feedback or disagreements within a technical team?

Final Discussion

Two-way dialogue to assess fit and learn about company culture.

What to demonstrate

• Two-way dialogue to assess fit and learn about company culture
• Depth in Technical Interviewing

How to prepare

• Work Technical Interviewing until you can explain it without notes
• Work Programming Problem Solving until you can explain it without notes

Where candidates lose points

Think Aloud

During coding tasks, explain your reasoning. Interviewers want to see how you approach a problem, not just the code you produce.

Clarify Requirements

Before starting a technical task, ask questions. It shows you are thinking about edge cases and requirements.

Leverage Tools

In some technical sessions, you may have access to research tools. Use them professionally to support your problem-solving process.

Be Concise

When answering behavioral questions, use the STAR method (Situation, Task, Action, Result) to keep your answers structured and impactful.

Questions & practice

Can you walk me through your approach to solving this algorithmic challenge?

Medium · Technical & Algorithmic Proficiency

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. 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 optimize this function for better performance or lower memory usage?

Medium · Technical & Algorithmic Proficiency

Approach

1. Say what the runtime actually does before reasoning about the code.
2. Name what is shared across threads and what owns each piece of state.
3. Identify the window where an invariant is briefly untrue.
4. 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?

Please explain your choice of data structure for this specific problem.

Medium · Technical & Algorithmic Proficiency

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. 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?

Find version gaps and relay lag with window functions

Medium · window functions · event tables · frame semantics

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

1. 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.
2. 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.
3. 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.
4. 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?

Write the update path that detects a concurrent edit

Medium · optimistic concurrency · transactional outbox · audit history

resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.

Approach

1. One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
2. Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
3. State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
4. Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.

Follow-up

• A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
• Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?

Convert the listing endpoint from offset pages to stable cursors

Medium · pagination · cursors · index access path

GET /v1/resources returns a tenant's resources newest-updated first, today with page and per_page, backed by index (tenant_id, status, updated_at DESC, resource_id DESC). Callers are a browser feed and a nightly sync job that walks every page. Users report items appearing twice or vanishing between pages, and page 400 is slow. Design the cursor contract: what the cursor contains and how it is encoded, the exact WHERE and ORDER BY, what happens when a row's updated_at changes mid-walk, how a client detects the end, and what the sync job does when a cursor is rejected.

Approach

1. Separate the two defects, because they have different fixes. Cost: OFFSET n makes the engine produce and discard n rows, so price grows with page depth rather than page size and page 400 pays for 400 pages of work. Correctness: while the set shifts, rows cross the offset boundary and are skipped or repeated, and nothing in the response lets the client detect it.
2. Write the seek: WHERE tenant_id = $1 AND status = $2 AND (updated_at, resource_id) < ($k, $id) ORDER BY updated_at DESC, resource_id DESC LIMIT n. The tie-break is not decoration - updated_at is not unique, and two rows sharing a timestamp across a page boundary reintroduce exactly the skip this was adopted to remove. PostgreSQL seeks the composite index on the row-value comparison directly; on an engine that does not optimise a row constructor, expand it into the equivalent OR form or the plan quietly degrades to a scan.
3. Encode the cursor as an opaque token carrying the sort key, the id, and a fingerprint of the filter and sort order, signed or at minimum validated. A cursor replayed against a different sort or filter must be a 400 with its own code, not a silently wrong page - the sync job cannot notice the difference otherwise.
4. State the guarantee precisely rather than generously. Keyset is stable against inserts and deletes elsewhere in the set, because the position is a value and not a count. It is not a snapshot: updated_at is mutable, so a row that is edited during the walk re-sorts and may be seen twice or not at all. If the sync job needs exactly-once coverage, order on an immutable key such as (created_at, resource_id), or walk resource_revision by revision_id and treat updated_at as data.

Follow-up

• The client wants a total count and the ability to jump to page 400. What can you honestly offer instead, and what does each option cost?
• How do you paginate backwards, and what does that require of the index?

Choose what to break when replication lag reaches forty seconds

Hard · replication lag · read-after-write · consistency vs availability

Reads are served from two replicas: 14k requests/second, about 85% absorbed by cache, so roughly 2.1k reads/second reach the database. Writes go to the primary at 1.2k/second. A tenant's backfill drives replication lag from under 100 ms to 40 seconds and it is still climbing. Sessions that have just written are pinned to the primary. Decide, endpoint class by endpoint class, whether to serve stale, fail, or route to the primary, and justify each choice with the load it adds to the primary. Then state what you would have built beforehand.

Approach

1. Establish blast radius before cause, because mitigation and diagnosis have different deadlines. The decisive arithmetic is what happens if the database reads move to the primary: 2.1k reads/second on top of 1.2k writes/second roughly triples its operation count, on the node already absorbing the backfill that caused this. Reads and writes are not equal in cost, so treat that as an argument against a blanket move rather than as a capacity model - but it is enough to rule out routing everything to the primary.
2. Classify endpoints by what staleness costs, not by how important they feel. Reads whose staleness is invisible - listings, search, counters - stay on the replica and return the watermark so the client can tell. Reads that immediately follow that same session's write keep their primary pin, which is a small bounded slice of traffic rather than the whole 2.1k/second. Reads that feed a decision with a side effect - authorisation, quota, the read half of a read-modify-write - must not be stale at all, because a 40-second-old permission row is the stale-permission failure wearing a different costume; those go to the primary or fail.
3. Shed instead of queueing. If the must-be-fresh class alone exceeds the primary's headroom, refuse its lowest-value slice with 503 and a retry-after. A request queued behind a saturated primary holds a connection for a client that has already given up, and the retry storm that follows is what turns degradation into an outage. Bound the connection pool per role so the read fallback cannot consume the write path's connections - that bulkhead is the single decision that determines whether writes survive the next ten minutes.
4. Attack the cause in parallel, since it is the one thing that can be stopped. The backfill is the load generator. A backfill that reads replication lag as its throttle signal and pauses above a threshold would have made this a non-event, with batch sizes small enough that each batch's write volume is a fraction of what a replica can apply per second. That is most of the answer to what should have existed beforehand.

Follow-up

• Lag returns to normal in nine minutes. Which mitigation do you remove first, and which one stays permanently?
• A user reports their change did not save, and the write committed. Trace the path that produces that report and name the signal that would have shown it before the report arrived.

Listing latency scales with page size, not with filters

Easy · n+1 · latency · query batching

The tenant listing endpoint reads resource filtered by tenant_id and status, ordered by updated_at DESC, and returns each row plus the owner's display name from app_user and the actor of that resource's latest resource_revision. p99 is 55 ms at 10 rows per page and 1.4 s at 200. Database telemetry shows 401 statements per request, each under 1 ms, and nothing in the slow-query log. Diagnose the cause and give the fix, stating the statement count per request and the p99 you expect afterwards.

Approach

1. Read the counters before forming a theory. 401 statements for 200 rows is one driver query plus two per row, and sub-millisecond execution with an empty slow-query log rules out a bad plan. The time is round trips, which is why it is invisible in every per-query metric and scales with rows returned rather than with filter selectivity.
2. Name the two per-row statements from their normalised text: a single-row app_user lookup by user_id, and a resource_revision lookup by resource_id ordered by version DESC LIMIT 1. Confirm by dropping those two response fields and watching the statement count fall to one. That locates the calls in the serialisation layer, not the repository.
3. Check that the arithmetic accounts for the whole gap. Measure one round trip to the replica in isolation; 400 trips at roughly 3 ms of network plus 0.2 ms of execution is about 1.3 s on top of a 55 ms baseline, which matches. If the multiplication had fallen short, the N+1 would only be part of the story and you would keep looking.
4. Batch both lookups. Collect owner_user_ids and resource_ids from the driver query, then issue WHERE tenant_id = $1 AND user_id = ANY($2) for the users, and PostgreSQL's SELECT DISTINCT ON (resource_id) ... WHERE resource_id = ANY($2) ORDER BY resource_id, version DESC for the latest revision, which the UNIQUE (resource_id, version) index serves directly. On an engine without DISTINCT ON, use a lateral join or a row_number window. Three statements per request at any page size.

Follow-up

• The page size is capped at 200 today. What breaks first if it is raised to 2,000, and is it still this bug?
• How do you stop the next N+1 from reaching production, given that no individual query is slow and the endpoint's tests pass?

Suggested practice checklist

Built from the rounds and topics Kis Solutions candidates report.

Day 1 — Map the Kis Solutions loop

• Write out the reported sequence: Initial Assessment, Technical Evaluation, Engagement with Recruiters, Skill Demonstration, Final Discussion.
• 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 5 reported rounds, with the weakest marked.

Day 2 — Work Technical Interviewing

• Spend the session on Technical Interviewing, which Kis Solutions candidates report being tested on.
• Write one worked example in Technical Interviewing and time yourself on it.

Deliverable: One timed worked example in Technical Interviewing.

Day 3 — Work Programming Problem Solving

• Spend the session on Programming Problem Solving, which Kis Solutions candidates report being tested on.
• Write one worked example in Programming Problem Solving and time yourself on it.

Deliverable: One timed worked example in Programming Problem Solving.

Day 4 — Work Algorithmic Thinking

• Spend the session on Algorithmic Thinking, which Kis Solutions candidates report being tested on.
• Write one worked example in Algorithmic Thinking and time yourself on it.

Deliverable: One timed worked example in Algorithmic Thinking.

Day 5 — Answer out loud: Technical & Algorithmic Proficiency

• Answer aloud, timed: Can you walk me through your approach to solving this algorithmic challenge?
• Answer aloud, timed: How would you optimize this function for better performance or lower memory usage?

Deliverable: Spoken answers to 2 reported Technical & Algorithmic Proficiency question(s), under time.

Day 6 — Answer out loud: Behavioral & Professional Experience

• Answer aloud, timed: Could you tell me about your professional journey and the experiences that led you here?
• Answer aloud, timed: Can you describe a challenging technical project you managed and how you overcame obstacles?

Deliverable: Spoken answers to 2 reported Behavioral & Professional Experience question(s), under time.

Day 7 — Dry run for Kis Solutions

• Run one full mock under time, then write down the two questions you most want to ask your interviewers.

Deliverable: A completed timed mock and two questions to ask.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

How do you handle edge cases when writing code for production?

Medium · Technical & Algorithmic Proficiency

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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?

Could you tell me about your professional journey and the experiences that led you here?

Medium · Behavioral & Professional Experience

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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?

Can you describe a challenging technical project you managed and how you overcame obstacles?

Medium · Behavioral & Professional Experience

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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 joining the team at Kis Solutions?

Medium · Behavioral & Professional Experience

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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 or disagreements within a technical team?

Medium · Behavioral & Professional Experience

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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?