Interview guides · Kirey

Kirey Software Engineer Interview Guide

Kirey Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at Kirey, you are at the heart of the company’s mission to deliver complex digital transformation projects. You will be responsible for designing, developing, and maintaining robust software solutions that address the specific needs of diverse clients. Your work directly impacts the scalability and efficiency of the systems that our partners rely on to maintain their competitive edge in the market. This role requires a blend of technical precision and collaborative problem-solving. Whether you are working with core Java frameworks or modern frontend technologies, you will be expected to contribute to the entire software development lifecycle. At Kirey, we value engineers who can bridge the gap between abstract requirements and clean, high-performance code, ensuring that our technical delivery remains synonymous with quality and reliability.

This guide is scoped to a Software Engineer candidate at Kirey.

Focus areas

Java
Backend Fundamentals (Java/Spring/ORM)
Object-Oriented Programming (OOP)

The Kirey interview process

Kirey candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Introductory Call

Initial call to align on your background and the company’s values.

What to demonstrate

Initial call to align on your background and the company’s values
Depth in Java

How to prepare

Answer aloud and timed: How do you manage memory and performance in Java applications?
Answer aloud and timed: What are the key differences between various lifecycle hooks in Angular?

Technical Assessment

Evaluation of technical skills to ensure competency in relevant areas.

What to demonstrate

Evaluation of technical skills to ensure competency in relevant areas
Depth in Java

How to prepare

Answer aloud and timed: Can you explain how you would optimize a complex SQL query?
Answer aloud and timed: How do you handle dependency injection in Spring?

Final Discussions

Manager-led discussions focusing on behavioral narratives and fit.

What to demonstrate

Manager-led discussions focusing on behavioral narratives and fit
Depth in Java

How to prepare

Answer aloud and timed: What are the common pitfalls when working with asynchronous JavaScript?
Answer aloud and timed: How do you structure a web application for better maintainability?

Where candidates lose points

Own your experience

Be prepared to discuss your past projects in depth; the best candidates can explain the trade-offs they made during development.

Practice communication

During technical rounds, "think out loud." Interviewers want to see your logic, not just the final result.

Research the company

Familiarize yourself with the projects and values of Kirey. Showing genuine interest in what we do goes a long way.

Questions & practice

How do you manage memory and performance in Java applications?

Medium · Technical Fundamentals

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?

What are the common pitfalls when working with asynchronous JavaScript?

Medium · Technical Fundamentals

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?

Find overlapping job attempts and peak concurrency from lease records

Medium · sweep line · intervals · leases

A day of job_run history yields about 50,000,000 attempt records: (job_run_id, job_type, attempt, started_at, finished_at which is NULL when the worker died, lease_expires_at). Leases expire on a clock, so a job that outran its lease ran twice. Produce (a) every job_run_id whose attempts overlapped in wall-clock time and (b) the peak number of simultaneously running attempts per job_type with the minute it occurred. Target O(n log n). State how you treat a NULL finished_at and what clock skew does to your answer.

Approach

Define the interval before sorting anything: an attempt occupies [started_at, COALESCE(finished_at, lease_expires_at)). finished_at is observed and lease_expires_at is only a promise, so every attempt without a finish contributes an estimate and the whole result is a lower bound on overlap rather than an exact count.
For peak concurrency, sweep: emit 2n endpoints, sort by (timestamp, kind) with ends ordered before starts at equal timestamps, then walk the sequence maintaining a counter per job_type and record each type's maximum with its timestamp. O(n log n) dominated by the sort, O(n) space, or O(1) extra if the sort is external and the walk streams.
For overlap detection, do not compare attempts pairwise. A single global sort by (job_run_id, started_at) gives both the grouping and the order; within a group, keep the maximum end seen so far and report an overlap exactly when the next start is less than that running maximum, which is one linear pass after the sort.
Half-open intervals matter and are easy to get wrong: with closed intervals an attempt ending at the same millisecond another begins reads as concurrency two, and across 50,000,000 records that artefact swamps the real signal.

Follow-up

A handler is not idempotent and you have found 400 overlapping jobs. Which of them actually caused damage, and what would you query to find out?
Peak concurrency for one job_type is 4 against a configured cap of 4. Is the cap working, or is the data hiding attempts that never started?

Can you explain how you would optimize a complex SQL query?

Medium · Technical Fundamentals

Approach

Name the grain you start from and join outward from it.
Check whether any join is one-to-many before aggregating, or the sums inflate.
Say which index the query would use, and what makes it unusable.
Handle the rows that do not match: that is usually the actual question.

Follow-up

How does the query change if that join becomes one-to-many?
What happens to this when the table is ten times larger?

Replace offset paging on the resource feed with keyset

Easy · keyset pagination · composite index · sort order

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?

What are the key differences between various lifecycle hooks in Angular?

Medium · Technical Fundamentals

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 structure a web application for better maintainability?

Medium · Software Architecture & Design

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 is your approach to designing a system with a mocked backend?

Medium · Software Architecture & Design

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 code follows SOLID principles?

Medium · Software Architecture & Design

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 feature delivery speed with long-term technical debt?

Medium · Software Architecture & Design

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?

Every query on one table stalls for forty seconds mid-deploy

Medium · lock contention · ddl · migrations

During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.

Approach

Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.

Follow-up

The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?

Suggested practice checklist

Built from the rounds and topics Kirey candidates report.

Day 1 — Map the Kirey loop

Write out the reported sequence: Introductory Call, Technical Assessment, Final Discussions.
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.

Day 2 — Work Java

Spend the session on Java, which Kirey candidates report being tested on.
Write one worked example in Java and time yourself on it.

Deliverable: One timed worked example in Java.

Day 3 — Work Backend Fundamentals (Java/Spring/ORM)

Spend the session on Backend Fundamentals (Java/Spring/ORM), which Kirey candidates report being tested on.
Write one worked example in Backend Fundamentals (Java/Spring/ORM) and time yourself on it.

Deliverable: One timed worked example in Backend Fundamentals (Java/Spring/ORM).

Day 4 — Work Object-Oriented Programming (OOP)

Spend the session on Object-Oriented Programming (OOP), which Kirey candidates report being tested on.
Write one worked example in Object-Oriented Programming (OOP) and time yourself on it.

Deliverable: One timed worked example in Object-Oriented Programming (OOP).

Day 5 — Answer out loud: Technical Fundamentals

Answer aloud, timed: How do you manage memory and performance in Java applications?
Answer aloud, timed: What are the key differences between various lifecycle hooks in Angular?

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

Day 6 — Answer out loud: Software Architecture & Design

Answer aloud, timed: How do you structure a web application for better maintainability?
Answer aloud, timed: What is your approach to designing a system with a mocked backend?

Deliverable: Spoken answers to 2 reported Software Architecture & Design question(s), under time.

Day 7 — Answer out loud: Behavioral & Cultural Fit

Answer aloud, timed: Describe a time you had to explain a technical concept to a non-technical stakeholder.
Answer aloud, timed: How do you handle disagreements regarding architectural decisions within your team?

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

Behavioural preparation

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

How do you handle dependency injection in Spring?

Medium · Technical Fundamentals

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?

Can you describe a time you had to refactor a legacy module?

Medium · Software Architecture & Design

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?