One Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at One, you will build and scale financial technology systems designed to provide accessible, seamless banking and credit services. The engineering team operates at the intersection of complex financial infrastructure, high-throughput distributed systems, and real-time user applications. You will be responsible for building resilient microservices, designing reliable APIs, and ensuring strict data consistency across platforms handling sensitive financial transactions. The impact of this role is immediate and broad. Whether you are engineering backend services in Node.js, Java, or Python, modeling transactional data structures, or developing cross-platform client experiences in React Native, your code directly influences how users manage their money.

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

Focus areas

• Data Structures (Arrays, Lists, Hashmaps)
• System Design
• Low-Level Design (LLD)

The One interview process

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

Initial Technical Screening

Conducted by Karat, this round focuses on live coding, debugging, and low-level problem solving.

What to demonstrate

• Conducted by Karat, this round focuses on live coding, debugging, and low-level problem solving
• Depth in Data Structures (Arrays, Lists, Hashmaps)

How to prepare

• Answer aloud and timed: Given an array of integers, write a function to find the $k$-th largest element.
• Answer aloud and timed: Identify the most frequent element across multiple input arrays of numbers.

Full Interview Loop

Candidates who pass the initial screen engage in deeper discussions on system design, past experiences, and behavioral alignment.

What to demonstrate

• Candidates who pass the initial screen engage in deeper discussions on system design, past experiences, and behavioral alignment
• Depth in Data Structures (Arrays, Lists, Hashmaps)

How to prepare

• Answer aloud and timed: Write a function to iterate through a matrix based on specific row and column instructions.
• Answer aloud and timed: Given a nested JSON structure of arbitrary depth containing objects and arrays, write a recursive function to extract all keys where the value is null.

Executive Interviews

Final stages involve conversations with senior engineering leaders or founders to assess cultural fit.

What to demonstrate

• Final stages involve conversations with senior engineering leaders or founders to assess cultural fit
• Depth in Data Structures (Arrays, Lists, Hashmaps)

How to prepare

• Answer aloud and timed: Solve a greedy-style path optimization problem (e.g., calculate the minimum number of fuel stations needed to complete a long-distance journey).
• Answer aloud and timed: Design a highly available, distributed rate limiter service to throttle access to sensitive API endpoints.

Where candidates lose points

Master timed code reading

Practice picking up unknown codebases and identifying logic errors quickly. The screen emphasizes fast comprehension alongside code writing.

Be concrete in system design

Avoid high-level hand-waving. Clearly write down data schemas, define key API endpoints, and specify how your system handles errors and rate limits.

Prepare clear past project stories

Be ready to detail your contributions to previous initiatives, highlighting trade-offs made, tech debt handled, and business outcomes achieved.

Watch out for floating-point calculations and string formatting edge cases in practical coding tasks

Always review existing unit test files to identify expected outputs.

Questions & practice

Given an array of integers, write a function to find the $k$-th largest element.

Medium · Data Structures & Practical Algorithms

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?

Identify the most frequent element across multiple input arrays of numbers.

Medium · Data Structures & Practical Algorithms

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?

Write a function to iterate through a matrix based on specific row and column instructions.

Medium · Data Structures & Practical Algorithms

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 nested JSON structure of arbitrary depth containing objects and arrays, write a recursive function to

Medium · Data Structures & Practical Algorithms

Given a nested JSON structure of arbitrary depth containing objects and arrays, write a recursive function to extract all keys where the value is null.

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?

Solve a greedy-style path optimization problem (e.g., calculate the minimum number of fuel stations needed to

Medium · Data Structures & Practical Algorithms

Solve a greedy-style path optimization problem (e.g., calculate the minimum number of fuel stations needed to complete a long-distance journey).

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?

Walk through the boot process of an operating system or low-level runtime execution details.

Medium · Past Experience & Systems Deep Dives

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 core asynchronous programming concepts in JavaScript/Node.js, including callbacks, promise resolution,

Medium · Past Experience & Systems Deep Dives

Explain core asynchronous programming concepts in JavaScript/Node.js, including callbacks, promise resolution, and the event loop.

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?

Denormalise tenant onto revisions and backfill it live

Hard · denormalisation · online migration · backfill

resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.

Approach

1. Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
2. Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
3. Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
4. Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.

Follow-up

• The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
• How do you verify the backfill actually finished, given rows are still being inserted while it runs?

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 highly available, distributed rate limiter service to throttle access to sensitive API endpoints.

Medium · System Design & Architecture

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?

Design an in-memory or distributed caching system, detailing eviction policies and cache invalidation strategi

Medium · System Design & Architecture

Design an in-memory or distributed caching system, detailing eviction policies and cache invalidation strategies.

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 the data models and backend APIs for a core banking application handling balance checks and transfers.

Medium · System Design & 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?

Describe how you would model relational tables for an application and structure data access layer logic.

Medium · System Design & 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 real-time device management system backend using Node.js and Express.js.

Medium · System Design & 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?

Describe a challenging technical problem you solved in a past role, focusing on trade-offs and final outcomes.

Medium · Past Experience & Systems Deep Dives

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 balance tech debt remediation against aggressive feature delivery deadlines?

Medium · Past Experience & Systems Deep Dives

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?

Fix failing unit tests within a provided application codebase, focusing on edge cases such as floating-point p

Medium · Hands-on Coding, Debugging & API Develop

Fix failing unit tests within a provided application codebase, focusing on edge cases such as floating-point precision formatting.

Approach

1. Establish what changed and when, before forming any theory.
2. Pick a bisection that eliminates candidates whichever way it turns out.
3. Check the instrumentation before believing the symptom.
4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

• What would you look at first, and what would it rule out?
• How would you tell a cause from a coincidence here?

Implement stubbed-out methods in an automated highway toll booth system to compute fares based on base classes

Medium · Hands-on Coding, Debugging & API Develop

Implement stubbed-out methods in an automated highway toll booth system to compute fares based on base classes and defined data structures.

Approach

1. Establish what changed and when, before forming any theory.
2. Pick a bisection that eliminates candidates whichever way it turns out.
3. Check the instrumentation before believing the symptom.
4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

• What would you look at first, and what would it rule out?
• How would you tell a cause from a coincidence here?

Create a full-stack task management module incorporating Role-Based Access Control (RBAC) using React and Node

Medium · Hands-on Coding, Debugging & API Develop

Create a full-stack task management module incorporating Role-Based Access Control (RBAC) using React and Node.js.

Approach

1. Establish what changed and when, before forming any theory.
2. Pick a bisection that eliminates candidates whichever way it turns out.
3. Check the instrumentation before believing the symptom.
4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

• What would you look at first, and what would it rule out?
• How would you tell a cause from a coincidence here?

Build an Express.js backend service from scratch based on a provided functional specification.

Medium · Hands-on Coding, Debugging & API Develop

Approach

1. Establish what changed and when, before forming any theory.
2. Pick a bisection that eliminates candidates whichever way it turns out.
3. Check the instrumentation before believing the symptom.
4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

• What would you look at first, and what would it rule out?
• How would you tell a cause from a coincidence here?

Read an existing repository, identify logic bugs under time constraints, and refactor the code to ensure all u

Medium · Hands-on Coding, Debugging & API Develop

Read an existing repository, identify logic bugs under time constraints, and refactor the code to ensure all unit tests pass cleanly.

Approach

1. Establish what changed and when, before forming any theory.
2. Pick a bisection that eliminates candidates whichever way it turns out.
3. Check the instrumentation before believing the symptom.
4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

• What would you look at first, and what would it rule out?
• How would you tell a cause from a coincidence here?

Suggested practice checklist

Built from the rounds and topics One candidates report.

Day 1 — Map the One loop

• Write out the reported sequence: Initial Technical Screening, Full Interview Loop, Executive Interviews.
• 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 (Arrays, Lists, Hashmaps)

• Spend the session on Data Structures (Arrays, Lists, Hashmaps), which One candidates report being tested on.
• Write one worked example in Data Structures (Arrays, Lists, Hashmaps) and time yourself on it.

Deliverable: One timed worked example in Data Structures (Arrays, Lists, Hashmaps).

Day 3 — Work System Design

• Spend the session on System Design, which One 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 4 — Work Low-Level Design (LLD)

• Spend the session on Low-Level Design (LLD), which One candidates report being tested on.
• Write one worked example in Low-Level Design (LLD) and time yourself on it.

Deliverable: One timed worked example in Low-Level Design (LLD).

Day 5 — Answer out loud: Data Structures & Practical Algorithms

• Answer aloud, timed: Given an array of integers, write a function to find the $k$-th largest element.
• Answer aloud, timed: Identify the most frequent element across multiple input arrays of numbers.

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

Day 6 — Answer out loud: System Design & Architecture

• Answer aloud, timed: Design a highly available, distributed rate limiter service to throttle access to sensitive API endpoints.
• Answer aloud, timed: Design an in-memory or distributed caching system, detailing eviction policies and cache invalidation strategies.

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

Day 7 — Answer out loud: Hands-on Coding, Debugging & API Development

• Answer aloud, timed: Fix failing unit tests within a provided application codebase, focusing on edge cases such as floating-point precision formatting.
• Answer aloud, timed: Implement stubbed-out methods in an automated highway toll booth system to compute fares based on base classes and defined data structures.

Deliverable: Spoken answers to 2 reported Hands-on Coding, Debugging & API Development question(s), under time.

Behavioural preparation

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

Explain your experience with infrastructure-as-code tools like Terraform and cloud architecture deployment.

Medium · Past Experience & Systems Deep Dives

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 time when you took initiative on a project without waiting for explicit management direction.

Medium · Behavioral & Cultural Alignment

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 would you respond if your engineering manager assigned you a task you believed was technically impossible

Medium · Behavioral & Cultural Alignment

How would you respond if your engineering manager assigned you a task you believed was technically impossible or highly impractical?

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 missed a project deadline. What caused the delay, and how did you communicate i

Medium · Behavioral & Cultural Alignment

Describe a situation where you missed a project deadline. What caused the delay, and how did you communicate it?

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?

Walk me through your favorite engineering project. What technical decisions are you most proud of?

Medium · Behavioral & Cultural Alignment

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 could you improve the codebase or design of an assignment you submitted earlier in this process?

Medium · Behavioral & Cultural Alignment

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?