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ICT Infracon Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at ICT Infracon, you serve as a core contributor to the company’s backend and full-stack development initiatives. This role is pivotal in maintaining the integrity and performance of the infrastructure-focused software solutions that drive the organization’s operations. You will be expected to bridge the gap between complex architectural requirements and functional code, ensuring that every deployment is robust, scalable, and secure. The work environment at ICT Infracon is technically rigorous, placing a premium on deep expertise in the Java ecosystem. You will likely find yourself working on projects that require seamless integration between frontend interfaces and sophisticated backend frameworks.

This guide is scoped to a Software Engineer candidate at ICT Infracon.

Focus areas

  • Java
  • Spring Boot
  • Advanced Java

The ICT Infracon interview process

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

Technical Fundamentals Assessment

Initial assessment of your technical fundamentals to gauge core knowledge.

What to demonstrate

  • Initial assessment of your technical fundamentals to gauge core knowledge
  • Depth in Java

How to prepare

  • Answer aloud and timed: Explain the fundamental principles of OOPs (Object-Oriented Programming) and how you implement them in your code.
  • Answer aloud and timed: How do you handle exception handling in Java to ensure application stability?

Framework Deep Dive

In-depth exploration of specific frameworks relevant to the role.

What to demonstrate

  • In-depth exploration of specific frameworks relevant to the role
  • Depth in Java

How to prepare

  • Answer aloud and timed: What is the difference between various Java collections (e.g., List, Set, Map), and when would you choose one over another?
  • Answer aloud and timed: Describe the lifecycle of a JSP and explain where Java code is typically embedded within a JSP file.

Professional Experience Discussion

Discussion of your professional experience and how it relates to the position.

What to demonstrate

  • Discussion of your professional experience and how it relates to the position
  • Depth in Java

How to prepare

  • Answer aloud and timed: Can you explain the role of Hibernate in an enterprise application and how it manages persistence?
  • Answer aloud and timed: How do you structure a Spring Boot application to ensure modularity and ease of maintenance?

Theoretical Questions

Answering theoretical questions that reflect the responsibilities of a Software Engineer.

What to demonstrate

  • Answering theoretical questions that reflect the responsibilities of a Software Engineer
  • Depth in Java

How to prepare

  • Answer aloud and timed: What are the key differences between Angular and other frontend frameworks, and how do you integrate them with a Java backend?
  • Answer aloud and timed: Describe how you manage state and data flow in your web applications using JavaScript.

Practical Coding Tasks

Engagement in practical coding tasks to demonstrate problem-solving skills.

What to demonstrate

  • Engagement in practical coding tasks to demonstrate problem-solving skills
  • Depth in Java

How to prepare

  • Answer aloud and timed: Can you walk me through your approach to solving pattern matching problems?
  • Answer aloud and timed: How would you implement a standard algorithm for sorting or searching an array?

Complex Questions

Introduction of more complex architectural or design-related questions based on performance.

What to demonstrate

  • Introduction of more complex architectural or design-related questions based on performance
  • Depth in Java

How to prepare

  • Answer aloud and timed: Can you demonstrate the logic behind swapping two numbers without using a temporary variable?
  • Answer aloud and timed: Given a specific scenario, how would you design a database query to optimize performance in SQL?

Where candidates lose points

Communicate your thought process

If you are stuck on a coding problem, explain what you are thinking. We value the logic you use to reach a solution as much as the solution itself.

Be honest about your skills

If you are not familiar with a specific tool, it is better to admit it and explain how you would learn it rather than guessing.

Review your basics

Do not overlook core OOPs concepts or basic Java collections; these are common areas where candidates stumble.

Focus on project impact

When discussing your past work, emphasize the results of your contributions rather than just the tasks you performed.

Questions & practice

Can you walk me through your approach to solving pattern matching problems?

Medium · Problem Solving & Technical Logic

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 implement a standard algorithm for sorting or searching an array?

Medium · Problem Solving & Technical Logic

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?

Can you demonstrate the logic behind swapping two numbers without using a temporary variable?

Medium · Problem Solving & Technical Logic

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?

Given a specific scenario, how would you design a database query to optimize performance in SQL?

Medium · Problem Solving & Technical Logic

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. 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

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

Explain the fundamental principles of OOPs (Object-Oriented Programming) and how you implement them in your co

Medium · Core Java & Advanced Programming

Explain the fundamental principles of OOPs (Object-Oriented Programming) and how you implement them in your code.

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

What is the difference between various Java collections (e.g., List, Set, Map), and when would you choose one

Medium · Core Java & Advanced Programming

What is the difference between various Java collections (e.g., List, Set, Map), and when would you choose one over another?

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

Describe the lifecycle of a JSP and explain where Java code is typically embedded within a JSP file.

Medium · Core Java & Advanced Programming

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

Can you explain the role of Hibernate in an enterprise application and how it manages persistence?

Medium · Core Java & Advanced Programming

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 Spring Boot application to ensure modularity and ease of maintenance?

Medium · Web Development & Frameworks

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

What are the key differences between Angular and other frontend frameworks, and how do you integrate them with

Medium · Web Development & Frameworks

What are the key differences between Angular and other frontend frameworks, and how do you integrate them with a Java backend?

Approach

  1. Say who the caller is and what they do when the call fails halfway.
  2. Define the identity of a request so a retry cannot double-apply it.
  3. Separate accepted, pending, failed and confirmed; they are different facts.
  4. Design the error taxonomy before the success shape; callers branch on it.

Follow-up

  • What happens if the caller retries after a timeout?
  • How does a client discover it is on an old version of this contract?

Describe how you manage state and data flow in your web applications using JavaScript.

Medium · Web Development & Frameworks

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

Read latency spikes on a sixty-second sawtooth

Medium · cache stampede · single-flight · ttl

The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.

Approach

  1. Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
  2. Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
  3. Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
  4. De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.

Follow-up

  • The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
  • How does your answer change if the recompute takes 4 seconds instead of 250 ms?

Suggested practice checklist

Built from the rounds and topics ICT Infracon candidates report.

Day 1 — Map the ICT Infracon loop

  • Write out the reported sequence: Technical Fundamentals Assessment, Framework Deep Dive, Professional Experience Discussion, Theoretical Questions, Practical Coding Tasks, Complex Questions.
  • 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 6 reported rounds, with the weakest marked.

Day 2 — Work Java

  • Spend the session on Java, which ICT Infracon 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 Spring Boot

  • Spend the session on Spring Boot, which ICT Infracon candidates report being tested on.
  • Write one worked example in Spring Boot and time yourself on it.

Deliverable: One timed worked example in Spring Boot.

Day 4 — Work Advanced Java

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

Deliverable: One timed worked example in Advanced Java.

Day 5 — Answer out loud: Core Java & Advanced Programming

  • Answer aloud, timed: Explain the fundamental principles of OOPs (Object-Oriented Programming) and how you implement them in your code.
  • Answer aloud, timed: How do you handle exception handling in Java to ensure application stability?

Deliverable: Spoken answers to 2 reported Core Java & Advanced Programming question(s), under time.

Day 6 — Answer out loud: Web Development & Frameworks

  • Answer aloud, timed: How do you structure a Spring Boot application to ensure modularity and ease of maintenance?
  • Answer aloud, timed: What are the key differences between Angular and other frontend frameworks, and how do you integrate them with a Java backend?

Deliverable: Spoken answers to 2 reported Web Development & Frameworks question(s), under time.

Day 7 — Answer out loud: Problem Solving & Technical Logic

  • Answer aloud, timed: Can you walk me through your approach to solving pattern matching problems?
  • Answer aloud, timed: How would you implement a standard algorithm for sorting or searching an array?

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

Behavioural preparation

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

How do you handle exception handling in Java to ensure application stability?

Medium · Core Java & Advanced Programming

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?

Ship under a deadline and bound the debt you chose

Medium · pagination · technical debt · tradeoffs

You have four days to ship a tenant-facing listing endpoint. The version you would defend uses keyset pagination over (tenant_id, status, updated_at DESC, resource_id DESC); the version you can finish uses LIMIT/OFFSET with no matching index. Describe a deadline call you actually made of this shape: what you shipped, what you knowingly deferred, how you bounded the damage with a mechanism rather than an intention, and the specific numeric condition that would force the follow-up. Name who you told and where you wrote it down.

Approach

  1. Name the deferred failure precisely instead of calling it slow. OFFSET n makes the database produce and discard n rows, so cost grows with page depth; without an index matching the sort, every matching row is read and sorted before the limit applies; and rows inserted between two page fetches shift across the boundary so items are skipped or repeated with nothing in the response to signal it.
  2. Bound the blast radius with something mechanical rather than a promise: cap maximum page depth, cap page size, restrict the endpoint to one internal caller, or keep it behind a flag. State which failure each cap removes and which it leaves standing.
  3. Attach a number to the trigger and wire it to an alarm: the first tenant crossing N resources, or the endpoint's p99 crossing its share of the 400 ms budget, so the debt announces itself instead of waiting to be remembered.
  4. Write it where the next engineer looks, which is the code and the ticket, not a chat message: what was deferred, why, the cap, and the trigger.

Follow-up

  • At what page depth does the offset version breach your latency budget, given your page size and row counts?
  • What breaks first when you switch to keyset pagination later, and what does a client holding an old page token see?

Unblock an engineer without taking the keyboard

Easy · mentoring · leases · at-least-once

A teammate has spent two days on a job handler that occasionally writes duplicate rows. They are certain the queue is delivering twice by mistake. You suspect a lease expiring under a slow handler, so the job is running concurrently with itself. Describe how you have unblocked someone in this position: what you asked before offering a hypothesis, what you showed them rather than told them, and what you left them owning. Then say what you would do if their theory turned out to be the right one.

Approach

  1. Ask before diagnosing, and ask for things answerable from data they already have: the attempt count on the job rows that produced duplicates, the handler's observed duration against its lease expiry, and whether the duplicate rows share a natural key that a unique constraint could have caught.
  2. Teach the shape rather than the answer. A lease cannot distinguish a dead worker from a slow one, so a handler that outruns its lease is running twice by design, and deploys deliver the other half by killing handlers mid-run on every rollout. Both of their candidate theories produce identical duplicate rows, which is why the evidence has to come from timings rather than from argument.
  3. Hand over a checklist they execute: a natural key on every write the handler performs so the second copy collides rather than appends, the record of intent written before any external effect, a lease heartbeat while running, and the metric that shows it working.
  4. Keep ownership with them deliberately. Pair on the first write, then step back; if you finish it yourself you have closed one ticket and left the same person stuck on the next redelivery.

Follow-up

  • How would you distinguish a genuine double-delivery from a lease expiry using only the data already stored?
  • Their handler calls an external endpoint before recording that it did. What do you tell them to change first?