Inc. In Software Engineer Interview Guide

The 60-second brief

At Inc. In, a Software Engineer is responsible for building and maintaining the foundational systems that power global commerce. The engineering team designs, develops, and scales highly secure, high-throughput transaction processing networks, merchant platforms, and developer-facing APIs. Operating at this level of scale requires writing clean, optimized, and incredibly resilient code, as even a few milliseconds of latency or a minor system failure can disrupt millions of payments worldwide. As a Software Engineer, you will work on complex distributed systems, cloud-native migrations, and high-performance database architectures. Your work directly impacts the reliability and security of financial transactions, requiring a deep understanding of fault tolerance, concurrency, and data integrity.

This guide is scoped to a Software Engineer candidate at Inc. In.

Focus areas

• Data Structures & Algorithms (DSA)
• Problem Solving / Algorithmic Reasoning
• System Design

The Inc. In interview process

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

Online Assessment

Automated assessment requiring you to solve three to four coding questions within 70 to 90 minutes.

What to demonstrate

• Automated assessment requiring you to solve three to four coding questions within 70 to 90 minutes
• Depth in Data Structures & Algorithms (DSA)

How to prepare

• Answer aloud and timed: Given an array of integers, find all unique triplets that sum to zero (3-Sum).
• Answer aloud and timed: Implement a Least Recently Used (LRU) Cache that supports get and put operations in O(1) time complexity.

Technical Conversations

Series of interviews evaluating your practical coding skills and theoretical computer science knowledge.

What to demonstrate

• Series of interviews evaluating your practical coding skills and theoretical computer science knowledge
• Depth in Data Structures & Algorithms (DSA)

How to prepare

• Answer aloud and timed: Given an array of numbers, find the contiguous subarray with the largest sum (Kadane’s Algorithm).
• Answer aloud and timed: Find the minimum window substring in a given string that contains all characters of another string.

Behavioral Conversations

Interviews focused on assessing your behavioral fit within the engineering organization.

What to demonstrate

• Interviews focused on assessing your behavioral fit within the engineering organization
• Depth in Data Structures & Algorithms (DSA)

How to prepare

• Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
• Re-read the description of the behavioral conversations above and write down what you would ask to confirm before it.

Where candidates lose points

Master SQL Window Functions

Do not overlook database questions. Candidates are frequently asked to write complex SQL queries on the spot, with a particular focus on window functions, joins, and aggregations.

Prepare for Proctoring

The online assessments on platforms like CodeSignal or HackerRank are strictly proctored. Ensure you take the test in a quiet, well-lit room with your camera and microphone enabled to avoid automated flag triggers.

Explain Trade-offs Explicitly

In system design interviews, there is rarely a single "correct" answer. Always present multiple approaches and clearly explain the trade-offs of each regarding latency, cost, and complexity.

If you encounter an interviewer who seems disengaged or asks unexpected technical trivia, remain calm and professional

Focus on explaining your fundamental computer science reasoning; showing a structured, logical approach is highly valued even if you do not know a specific definition.

Questions & practice

Given an array of integers, find all unique triplets that sum to zero (3-Sum).

Medium · Data Structures & Algorithms (DSA)

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?

Implement a Least Recently Used (LRU) Cache that supports get and put operations in O(1) time complexity.

Medium · Data Structures & Algorithms (DSA)

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 an array of numbers, find the contiguous subarray with the largest sum (Kadane’s Algorithm).

Medium · Data Structures & Algorithms (DSA)

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 the minimum window substring in a given string that contains all characters of another string.

Medium · Data Structures & Algorithms (DSA)

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 binary tree, write an algorithm to find its maximum height and verify if it is balanced.

Medium · Data Structures & Algorithms (DSA)

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?

Explain the difference between encapsulation and abstraction, and how they are implemented in Java.

Medium · Core Computer Science & Language Trivia

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?

What are the differences between malloc, calloc, and realloc in C, and how does JVM memory management compare?

Medium · Core Computer Science & Language Trivia

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?

Explain the difference between concurrency and asynchrony in multithreading.

Medium · Core Computer Science & Language Trivia

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?

Explain how a HashMap works internally, focusing on collision resolution and resizing.

Medium · Core Computer Science & Language Trivia

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?

Write an SQL query using window functions to find the top three maximum salaries within each department.

Medium · Core Computer Science & Language Trivia

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?

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?

Design a transaction management system for merchants that handles millions of payment events per second.

Medium · System Design & High-Level Architecture

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. 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 a system to handle large-scale data comparisons across heterogeneous file systems?

Medium · System Design & High-Level Architecture

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. 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?

Design a distributed resource scheduler that prevents race conditions and ensures high availability.

Medium · System Design & High-Level Architecture

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. 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 are the architectural challenges of migrating a monolithic application to microservices, and how do you a

Medium · System Design & High-Level Architecture

What are the architectural challenges of migrating a monolithic application to microservices, and how do you address them?

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. 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 a system to store string counts that returns minimum and maximum counts in O(1) time comp

Medium · System Design & High-Level Architecture

How would you design a system to store string counts that returns minimum and maximum counts in O(1) time complexity?

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. 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?

Talk about a complex technical project you owned from end to end. What architectural trade-offs did you make?

Medium · Behavioral & Teamwork

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. 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?

One log partition stops advancing while the others drain

Easy · poison message · head-of-line blocking · consumer lag

Search results for a subset of tenants are hours stale; the rest are current. The projection consumer reports lag of zero on 15 of 16 partitions and 400,000 on one. Its error rate is flat and its CPU is idle. outbox_event has no pending rows older than a second, so the relay has published everything it holds. Identify the mechanism, give the ordered checks, and state what you do in the first ten minutes versus what you change permanently.

Approach

1. Read the lag distribution first. A slow consumer lags everywhere; zero on fifteen partitions and 400,000 on one is not throughput. Idle CPU on the stuck partition means the consumer is not advancing its offset at all, which points at one message it cannot get past rather than at a rate problem.
2. Exonerate the producer before touching the consumer. No pending outbox rows older than a second means the relay published, so the event exists in the log. This separates never sent from sent and never applied, which are different code paths and usually different owners.
3. Read the message at the stuck offset and the handler's log lines for its event_id. A flat error rate with no progress has two explanations and you must distinguish them: the handler is throwing and the retry loop is swallowing it, or the handler is blocking on something and never returning. Idle CPU with no error lines favours the second.
4. Mitigate before diagnosing further. Move the offending event to a dead-letter store and commit the offset past it. Adding consumers does nothing here, because a partition is consumed by exactly one member of the group, and the blast radius is every aggregate hashed to that partition, not only the aggregate that produced the bad event.

Follow-up

• The dead-lettered event carried aggregate_version 7 and the projection had applied 6. What must the replay do differently if 8 and 9 landed in the meantime?
• How do you show staleness to the user while the partition is behind, given the API already returns the projection's watermark?

Suggested practice checklist

Built from the rounds and topics Inc. In candidates report.

Day 1 — Map the Inc. In loop

• Write out the reported sequence: Online Assessment, Technical Conversations, Behavioral Conversations.
• 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 Data Structures & Algorithms (DSA)

• Spend the session on Data Structures & Algorithms (DSA), which Inc. In candidates report being tested on.
• Write one worked example in Data Structures & Algorithms (DSA) and time yourself on it.

Deliverable: One timed worked example in Data Structures & Algorithms (DSA).

Day 3 — Work Problem Solving / Algorithmic Reasoning

• Spend the session on Problem Solving / Algorithmic Reasoning, which Inc. In candidates report being tested on.
• Write one worked example in Problem Solving / Algorithmic Reasoning and time yourself on it.

Deliverable: One timed worked example in Problem Solving / Algorithmic Reasoning.

Day 4 — Work System Design

• Spend the session on System Design, which Inc. In candidates report being tested on.
• Write one worked example in System Design and time yourself on it.

Deliverable: One timed worked example in System Design.

Day 5 — Answer out loud: Data Structures & Algorithms (DSA)

• Answer aloud, timed: Given an array of integers, find all unique triplets that sum to zero (3-Sum).
• Answer aloud, timed: Implement a Least Recently Used (LRU) Cache that supports get and put operations in O(1) time complexity.

Deliverable: Spoken answers to 2 reported Data Structures & Algorithms (DSA) question(s), under time.

Day 6 — Answer out loud: Core Computer Science & Language Trivia

• Answer aloud, timed: Explain the difference between encapsulation and abstraction, and how they are implemented in Java.
• Answer aloud, timed: What are the differences between malloc, calloc, and realloc in C, and how does JVM memory management compare?

Deliverable: Spoken answers to 2 reported Core Computer Science & Language Trivia question(s), under time.

Day 7 — Answer out loud: System Design & High-Level Architecture

• Answer aloud, timed: Design a transaction management system for merchants that handles millions of payment events per second.
• Answer aloud, timed: How would you design a system to handle large-scale data comparisons across heterogeneous file systems?

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

Behavioural preparation

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

Describe a time when you had to deliver a project under a tight deadline with incomplete requirements. How did

Medium · Behavioral & Teamwork

Describe a time when you had to deliver a project under a tight deadline with incomplete requirements. How did you manage?

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 a situation where you disagree with a senior engineer or team lead on a technical approach?

Medium · Behavioral & Teamwork

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?

Describe a situation where you had to learn a highly complex technology quickly without external guidance or t

Medium · Behavioral & Teamwork

Describe a situation where you had to learn a highly complex technology quickly without external guidance or tools.

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 Inc. In, and how do your career goals align with our engineering organizatio

Medium · Behavioral & Teamwork

Why are you interested in joining Inc. In, and how do your career goals align with our engineering organization?

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?