Sendbird Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at Sendbird, you will play a pivotal role in building and scaling the world's leading chat, voice, and video APIs. Sendbird powers real-time communication for billions of users across global applications, requiring an infrastructure that is incredibly reliable, low-latency, and highly scalable. Engineers here do not just write code; they design the foundational communication fabric that modern mobile and web applications rely on daily. In this role, you will work on complex distributed systems, high-throughput backend services, and developer-facing SDKs. Whether you are optimizing real-time message delivery protocols, building robust APIs, or working as a Content Engineer to create seamless developer integration experiences, your work directly impacts the developer ecosystem.

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

Focus areas

• Coding assessments
• Python
• Technical interviews

The Sendbird interview process

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

Recruiter Screen

Initial interaction to assess your background and fit for the role.

What to demonstrate

• Initial interaction to assess your background and fit for the role
• Depth in Coding assessments

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 Assessment

Evaluation of practical coding and integration skills.

What to demonstrate

• Evaluation of practical coding and integration skills
• Depth in Coding assessments

How to prepare

• Answer aloud and timed: Design an in-memory rate limiter to restrict API requests per user session.
• Answer aloud and timed: Find the longest consecutive sequence of online users from a real-time presence log.

Virtual Onsite Loop

Comprehensive series of interviews including technical deep dives and system design challenges.

What to demonstrate

• Comprehensive series of interviews including technical deep dives and system design challenges
• Depth in Coding assessments

How to prepare

• Answer aloud and timed: How would you design a scalable push notification service capable of delivering millions of payloads per minute?
• Answer aloud and timed: Explain how you would architect a real-time chat application using WebSockets, highlighting how you handle connection drops and state synchronization.

Where candidates lose points

Master the fundamentals of real-time communication

Be ready to explain the pros and cons of WebSockets, polling, and gRPC. Understanding how network protocols behave under poor connection conditions is highly relevant to our work.

Focus on Python concurrency

If you are interviewing for a role that emphasizes Python, make sure you are thoroughly familiar with asynchronous programming libraries, event loops, and concurrency paradigms.

When completing the take-home assignment, do not just aim for a working solution

Take the extra time to write clear comments, include basic unit tests, and document your architectural decisions.

Questions & practice

Implement a function to detect and resolve message delivery failures in a real-time chat queue.

Medium · Coding & Algorithmic Problem Solving

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 clean algorithm to handle real-time message deduplication across multiple client connections.

Medium · Coding & Algorithmic Problem Solving

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 longest consecutive sequence of online users from a real-time presence log.

Medium · Coding & Algorithmic Problem Solving

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 do you optimize asynchronous operations in Python to prevent blocking events in a high-concurrency environ

Medium · Technical Domain & Platform Setup

How do you optimize asynchronous operations in Python to prevent blocking events in a high-concurrency environment?

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 trade-offs between using SQL versus NoSQL databases for storing chat history.

Medium · Technical Domain & Platform Setup

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?

Explain why the owner filter ignores the listing index

Medium · composite index · query plans · sort elimination

The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.

Approach

1. Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
2. For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
3. Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
4. Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.

Follow-up

• 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
• A dashboard runs this for 40 owners in one page load. What changes about the design?

Design an in-memory rate limiter to restrict API requests per user session.

Medium · Coding & Algorithmic Problem Solving

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?

How would you design a scalable push notification service capable of delivering millions of payloads per minut

Medium · System Architecture & API Design

How would you design a scalable push notification service capable of delivering millions of payloads per minute?

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?

Explain how you would architect a real-time chat application using WebSockets, highlighting how you handle con

Medium · System Architecture & API Design

Explain how you would architect a real-time chat application using WebSockets, highlighting how you handle connection drops and state synchronization.

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 database schema and caching layer for a messaging platform that supports group chats with up to 100,0

Medium · System Architecture & API Design

Design a database schema and caching layer for a messaging platform that supports group chats with up to 100,000 members.

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 manage backpressure in a high-throughput data pipeline processing messaging analytics?

Medium · System Architecture & API Design

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?

Walk through the process of setting up the Sendbird SDK and configuring a basic chat client with custom featur

Medium · Technical Domain & Platform Setup

Walk through the process of setting up the Sendbird SDK and configuring a basic chat client with custom features.

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 would you debug a performance bottleneck in a third-party API integration?

Medium · Technical Domain & Platform Setup

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?

How do you receive and incorporate constructive feedback on your code or system designs?

Medium · Behavioral & Value Fit

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?

Every query on one table stalls for forty seconds mid-deploy

Medium · lock contention · ddl · migrations

During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.

Approach

1. Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
2. Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
3. Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
4. Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.

Follow-up

• The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
• Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?

Suggested practice checklist

Built from the rounds and topics Sendbird candidates report.

Day 1 — Map the Sendbird loop

• Write out the reported sequence: Recruiter Screen, Technical Assessment, Virtual Onsite 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 Coding assessments

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

Deliverable: One timed worked example in Coding assessments.

Day 3 — Work Python

• Spend the session on Python, which Sendbird candidates report being tested on.
• Write one worked example in Python and time yourself on it.

Deliverable: One timed worked example in Python.

Day 4 — Work Technical interviews

• Spend the session on Technical interviews, which Sendbird candidates report being tested on.
• Write one worked example in Technical interviews and time yourself on it.

Deliverable: One timed worked example in Technical interviews.

Day 5 — Answer out loud: Coding & Algorithmic Problem Solving

• Answer aloud, timed: Implement a function to detect and resolve message delivery failures in a real-time chat queue.
• Answer aloud, timed: Write a clean algorithm to handle real-time message deduplication across multiple client connections.

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

Day 6 — Answer out loud: System Architecture & API Design

• Answer aloud, timed: How would you design a scalable push notification service capable of delivering millions of payloads per minute?
• Answer aloud, timed: Explain how you would architect a real-time chat application using WebSockets, highlighting how you handle connection drops and state synchronization.

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

Day 7 — Answer out loud: Technical Domain & Platform Setup

• Answer aloud, timed: Walk through the process of setting up the Sendbird SDK and configuring a basic chat client with custom features.
• Answer aloud, timed: How do you optimize asynchronous operations in Python to prevent blocking events in a high-concurrency environment?

Deliverable: Spoken answers to 2 reported Technical Domain & Platform Setup question(s), under time.

Behavioural preparation

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

Describe a time when you had to make a critical technical trade-off to meet a tight product deadline.

Medium · Behavioral & Value Fit

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 a product manager or business analyst proposes a feature that is technical

Medium · Behavioral & Value Fit

How do you handle a situation where a product manager or business analyst proposes a feature that is technically unfeasible?

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?

Talk about a project where you had to quickly learn a new technology or programming language to deliver a solu

Medium · Behavioral & Value Fit

Talk about a project where you had to quickly learn a new technology or programming language to deliver a solution.

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?