Interview guides · Applegreen

Applegreen Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at Applegreen, you will be at the forefront of building robust, scalable systems that power seamless experiences for millions of customers. Applegreen is a dynamic and rapidly growing organization, and the technology team is essential to driving innovation across retail operations, customer loyalty programs, and enterprise logistics. Your work directly impacts how quickly and reliably services are delivered across a vast network of locations. The impact of this position extends far beyond writing code. You will contribute to high-availability point-of-sale systems, mobile application backends, and data-driven supply chain solutions. Because the business operates at a high transaction volume, the software you build must be resilient, secure, and optimized for performance.

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

Focus areas

Cost Engineering (General)
Software Engineering Fundamentals
Coding Practice

The Applegreen interview process

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

Recruiter Screen

Brief discussion to align on your background, expectations, and role logistics.

What to demonstrate

Brief discussion to align on your background, expectations, and role logistics
Depth in Cost Engineering (General)

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 Screening

Mix of conceptual questions and a straightforward coding exercise to establish baseline technical competency.

What to demonstrate

Mix of conceptual questions and a straightforward coding exercise to establish baseline technical competency
Depth in Cost Engineering (General)

How to prepare

Answer aloud and timed: How do you detect a cycle in a linked list?
Answer aloud and timed: Write a program to merge two sorted arrays into a single sorted array.

Onsite/Virtual Loop

Three to four sessions covering coding, system design, and behavioral questions with a focus on communication and culture fit.

What to demonstrate

Three to four sessions covering coding, system design, and behavioral questions with a focus on communication and culture fit
Depth in Cost Engineering (General)

How to prepare

Answer aloud and timed: Implement a simple LRU (Least Recently Used) cache.
Answer aloud and timed: Design a URL shortening service like Bitly.

Where candidates lose points

Think Out Loud

Your thought process is just as important as the final code. Always explain your logic, discuss potential edge cases, and outline your approach before you start typing.

Embrace the Conversational Tone

The interviewers want you to succeed. Treat the technical rounds like a collaborative working session. If an interviewer gives you a hint, take it gracefully and incorporate it into your solution.

Applegreen's recruiting team is known for exceptionally fast turnaround times

You can typically expect feedback within just a few days of your interview.

Prepare Your Questions

Always have questions ready for your interviewers. Asking about their current tech stack challenges, team structure, or upcoming projects shows genuine interest in the Software Engineer role.

Questions & practice

Write a function to reverse a string without using built-in reversal methods.

Medium · Coding Fundamentals

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
State the target complexity and say which constraint rules the naive version out.

Follow-up

How does this change if the input no longer fits in memory?
What is the worst case, and how likely is it on real data?

Given an array of integers, find two numbers that add up to a specific target sum.

Medium · Coding Fundamentals

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 do you detect a cycle in a linked list?

Medium · Coding Fundamentals

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
State the target complexity and say which constraint rules the naive version out.

Follow-up

How does this change if the input no longer fits in memory?
What is the worst case, and how likely is it on real data?

Write a program to merge two sorted arrays into a single sorted array.

Medium · Coding Fundamentals

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?

Implement a simple LRU (Least Recently Used) cache.

Medium · Coding Fundamentals

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
State the target complexity and say which constraint rules the naive version out.

Follow-up

How does this change if the input no longer fits in memory?
What is the worst case, and how likely is it on real data?

Write 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

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.
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.
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.
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?

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

Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.

Follow-up

Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?

Design a URL shortening service like Bitly.

Medium · System Design & Architecture

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 design the backend for a store locator feature on our mobile app?

Medium · System Design & Architecture

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?

Explain the difference between horizontal and vertical scaling, and when you would use each.

Medium · System Design & Architecture

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 handle a sudden spike in traffic to our customer loyalty portal?

Medium · System Design & Architecture

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
State the consistency you need, and where you are willing to be stale.

Follow-up

What breaks first when traffic grows ten times?
How does this behave when that dependency is down for an hour?

Describe how you would securely store and process user payment profiles.

Medium · System Design & Architecture

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?

p99 jumped on one listing filter while p50 stayed flat

Medium · query planning · composite index · percentiles

After a release that added an owner_user_id filter to the resource listing, p99 rose from 90 ms to 1.9 s while p50 stayed at 40 ms. Traffic and row counts are unchanged. resource carries the index (tenant_id, status, updated_at DESC, resource_id DESC). The new query filters tenant_id and owner_user_id, orders by updated_at DESC, resource_id DESC, and takes 20 rows. On PostgreSQL, explain the shape of the regression, prove it from a query plan, and give the index you would add.

Approach

Start from the shape. A flat p50 with a moved p99 means a subset of requests changed cost, not all of them, so the first job is naming the subset. Bucket the endpoint's latency by the tenant's row count; the natural hypothesis is that large tenants are a small share of requests and all of the tail.
Get the plan for the new query on a large tenant with EXPLAIN (ANALYZE, BUFFERS). Expect an index scan over the tenant's range, a filter discarding most of it, then a Sort feeding the Limit, possibly reporting Sort Method: external merge Disk. Read actual rows on the scan node, not estimated.
Explain why the existing index cannot serve it. A composite B-tree is seekable only as a left prefix, and with no equality predicate on status the scan cannot treat updated_at as an ordering, because rows in the tenant's range are ordered by status first. Everything matching must be read and sorted before LIMIT 20 can apply, so a tenant with 400,000 rows pays 400,000 rows to return 20.
Add (tenant_id, owner_user_id, updated_at DESC, resource_id DESC). Equality on the first two columns leaves the index ordered by updated_at within that pair, so the plan becomes an index scan that stops after 20 rows with no Sort node. PostgreSQL can scan a B-tree backwards, so the DESC markers matter only if the two sort columns ever disagree in direction; keeping them explicit documents the order the keyset cursor depends on.

Follow-up

The endpoint paginates with OFFSET. What does page 500 cost with your index, and what does the keyset version cost?
How would you have caught this before release, given that a 10,000-row seed database produces the same plan shape at an unnoticeable cost?

Suggested practice checklist

Built from the rounds and topics Applegreen candidates report.

Day 1 — Map the Applegreen loop

Write out the reported sequence: Recruiter Screen, Technical Screening, Onsite/Virtual Loop.
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 Cost Engineering (General)

Spend the session on Cost Engineering (General), which Applegreen candidates report being tested on.
Write one worked example in Cost Engineering (General) and time yourself on it.

Deliverable: One timed worked example in Cost Engineering (General).

Day 3 — Work Software Engineering Fundamentals

Spend the session on Software Engineering Fundamentals, which Applegreen candidates report being tested on.
Write one worked example in Software Engineering Fundamentals and time yourself on it.

Deliverable: One timed worked example in Software Engineering Fundamentals.

Day 4 — Work Coding Practice

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

Deliverable: One timed worked example in Coding Practice.

Day 5 — Answer out loud: Coding Fundamentals

Answer aloud, timed: Write a function to reverse a string without using built-in reversal methods.
Answer aloud, timed: Given an array of integers, find two numbers that add up to a specific target sum.

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

Day 6 — Answer out loud: System Design & Architecture

Answer aloud, timed: Design a URL shortening service like Bitly.
Answer aloud, timed: How would you design the backend for a store locator feature on our mobile app?

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

Day 7 — Answer out loud: Behavioral & Past Experience

Answer aloud, timed: Tell me about a time you had to deliver a project under a very tight deadline.
Answer aloud, timed: Describe a bug you had trouble finding. How did you eventually solve it?

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