Interview guides · Axians

Axians Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at Axians, you are joining a global organization known for its expertise in ICT solutions, ranging from cloud and cybersecurity to networking and digital transformation. Your role is pivotal in bridging the gap between complex client requirements and high-performance technical solutions. You will work within a collaborative, human-centric environment where technical proficiency is balanced with a deep commitment to project success and client satisfaction. This position is rarely about working in isolation; you will often find yourself collaborating with project managers, systems architects, and business unit leaders to deliver value.

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

Focus areas

Networking fundamentals
TCP vs UDP
Linux distributions

The Axians interview process

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

Recruiter Screen

Initial screening conducted by a recruiter or HR to assess fit for the role.

What to demonstrate

Initial screening conducted by a recruiter or HR to assess fit for the role
Depth in Networking fundamentals

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 Discussions

Technical discussions with managers or technical leads to evaluate skills and experience.

What to demonstrate

Technical discussions with managers or technical leads to evaluate skills and experience
Depth in Networking fundamentals

How to prepare

Answer aloud and timed: How do you handle a conflict with a project colleague?
Answer aloud and timed: What does the role of a manager mean to you?

Final Conversation

Potential final conversation with a site director or business unit head to discuss alignment and goals.

What to demonstrate

Potential final conversation with a site director or business unit head to discuss alignment and goals
Depth in Networking fundamentals

How to prepare

Answer aloud and timed: How do you spend your free time?
Answer aloud and timed: Can you describe your experience with Object-Oriented Programming (OOP) properties?

Where candidates lose points

Prepare your career story

Have a clear, concise narrative about your journey and why you are interested in Axians.

Research the location and team

Axians is decentralized; knowing about the specific branch or business unit you are interviewing with shows initiative.

Be honest about your skills

If you don't know an answer, admit it and explain how you would find the solution. This is often seen as a strength.

Ask meaningful questions

Use the interview as an opportunity to learn about the projects, the team culture, and the growth opportunities.

Questions & practice

What is the difference between TCP and UDP protocols?

Medium · Technical Proficiency and Problem Solvin

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?

What is your proficiency level with Linux distributions?

Medium · Technical Proficiency and Problem Solvin

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?

Collapse a redelivered event batch into per-aggregate high-water marks

Easy · hashing · at-least-once · aggregation

You drain a batch of up to 5,000,000 events, each (aggregate_id BIGINT, aggregate_version INT, event_type, payload). The log guarantees order within one aggregate only; the batch merges 64 partitions, and a relay failover has redelivered a range, so an older version for an aggregate can appear after a newer one. Given a map of last_applied_version per aggregate, produce the events worth applying, at most one per (aggregate_id, version), plus the count discarded. Target O(n) time. State the memory for 2,000,000 distinct aggregates and what you do when it does not fit.

Approach

One pass, one hash map from aggregate_id to the highest version kept, and a discard counter. An event whose version is at or below last_applied_version for its aggregate is dropped without further work, which is the whole reason the event carries its version rather than a delta. O(n) expected time, O(d) space in distinct aggregates.
Keep the maximum, never the last occurrence. The redelivered range means the final appearance of an aggregate in the batch can be an older version than one seen earlier in the same batch, so last-wins applies stale state over newer state and the projection regresses with no error anywhere.
Cost the memory instead of calling it large: an 8-byte key plus a 4-byte version is 12 bytes of payload, and an open-addressed table held at a 0.7 load factor costs roughly 17 bytes per entry before per-slot metadata, so 2,000,000 aggregates is tens of megabytes in a native layout and several times that in a runtime that boxes both key and value.
If the distinct set exceeds memory, partition on hash(aggregate_id) mod P and reduce each partition independently. Every event for one aggregate hashes to the same partition, so the per-partition result is exact and the merge is concatenation rather than a second reduction.

Follow-up

The payload is a patch rather than a snapshot, so applying only the highest version loses the intermediate changes. What changes in your reduction?
How do you detect that version 7 arrived while version 6 was never delivered, and what should the consumer do about the gap?

How would you approach an SQL query optimization task?

Medium · Technical Proficiency and Problem Solvin

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?

Keep soft-deleted accounts from blocking re-registration

Easy · soft delete · unique constraints · engine differences

app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.

Approach

Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.

Follow-up

A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
How do you honour an erasure request while resource_revision.actor_user_id still references this table?

Can you explain the concept of MVC architecture?

Medium · Technical Proficiency and Problem Solvin

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?

Tell us about your previous experience and how it prepared you for this role.

Medium · Experience and Methodology

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?

Do you prefer to follow instructions from experienced colleagues or take the initiative to solve problems inde

Medium · Experience and Methodology

Do you prefer to follow instructions from experienced colleagues or take the initiative to solve problems independently?

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 approach working within an Agile environment?

Medium · Experience and Methodology

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?

Are you familiar with specific networking or infrastructure protocols like IPMI?

Medium · Experience and Methodology

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?

Edge instances grow 400 MB per hour until the nightly restart

Hard · memory leak · heap analysis · metric cardinality

Edge API instances start at 700 MB resident and grow about 400 MB/hour; a nightly rolling restart has hidden it for weeks. Growth continues unchanged when request rate halves overnight, p99 degrades in the last hours before an instance is recycled, and heap used immediately after a forced full GC rises monotonically. The service holds no product state. Name the discriminating measurement that separates the plausible causes, give the most likely cause, and give the fix and how you would verify it.

Approach

Separate resident memory from live heap first, because they fail differently. Resident size can grow from fragmentation, native buffers or thread stacks while the heap is flat; heap used after a full GC rising monotonically is the measurement that says objects are reachable and not being released. You already have it, so this is retention, not fragmentation, and that closes off half the candidate list.
Use the rate's independence from traffic as the discriminator. Growth that continues at half the request rate rules out per-request objects that are merely slow to collect and points at a structure that grows with distinct values observed rather than with call volume. Write the candidates that have that property: a metrics registry keyed on a high-cardinality label, an unevicted cache, an interner, a per-key lock map.
Take two heap snapshots an hour apart and diff by retained size, reading the dominator tree, not by allocation count or instance count. Expect one root holding a map with millions of entries, then follow the reference chain to the code that inserts and never removes. Allocation profilers point at churn, which is the wrong signal here.
The candidate that fits this service is an observability label carrying an identifier, such as a request path recorded before templating so that /v1/resources/48213 becomes its own metric series. That grows with distinct ids seen, is independent of rate, and explains the late p99 degradation, since GC cost rises with the size of the live set.

Follow-up

Post-GC heap is now flat but resident size still creeps. What are you looking at, and does it matter?
How would you have detected this before an OOM, given the nightly restart masked the trend?

Suggested practice checklist

Built from the rounds and topics Axians candidates report.

Day 1 — Map the Axians loop

Write out the reported sequence: Recruiter Screen, Technical Discussions, Final Conversation.
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 Networking fundamentals

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

Deliverable: One timed worked example in Networking fundamentals.

Day 3 — Work TCP vs UDP

Spend the session on TCP vs UDP, which Axians candidates report being tested on.
Write one worked example in TCP vs UDP and time yourself on it.

Deliverable: One timed worked example in TCP vs UDP.

Day 4 — Work Linux distributions

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

Deliverable: One timed worked example in Linux distributions.

Day 5 — Answer out loud: Behavioral and Cultural Alignment

Answer aloud, timed: Why have you chosen to apply to Axians?
Answer aloud, timed: What are your professional aspirations for the next 5 to 10 years?

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

Day 6 — Answer out loud: Technical Proficiency and Problem Solving

Answer aloud, timed: Can you describe your experience with Object-Oriented Programming (OOP) properties?
Answer aloud, timed: What is the difference between TCP and UDP protocols?

Deliverable: Spoken answers to 2 reported Technical Proficiency and Problem Solving question(s), under time.

Day 7 — Answer out loud: Experience and Methodology

Answer aloud, timed: Tell us about your previous experience and how it prepared you for this role.
Answer aloud, timed: Do you prefer to follow instructions from experienced colleagues or take the initiative to solve problems independently?

Deliverable: Spoken answers to 2 reported Experience and Methodology question(s), under time.