As a Software Engineer at WATI, you play a pivotal role in shaping the future of customer engagement. WATI is at the forefront of building advanced conversational AI and messaging solutions, and your work directly impacts how businesses interact with their customers at scale. You will be responsible for building robust, high-performance systems that handle complex messaging workflows, ensuring reliability and speed for users worldwide. This role is both technically demanding and strategically significant. You will contribute to core products that require a deep understanding of distributed systems, backend architecture, and seamless integrations. Because WATI operates in a fast-paced environment, you will have the opportunity to influence product direction, solve challenging technical hurdles, and work alongside a team that values innovation, clean code, and user-centric problem-solving.
Initial Screening
reportedGauge your background and alignment with the role.
What to demonstrate
- Gauge your background and alignment with the role
- Depth in Backend Development
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 Rounds
reportedInvolve live coding, system design discussions, or deep dives into past projects.
What to demonstrate
- Involve live coding, system design discussions, or deep dives into past projects
- Depth in Backend Development
How to prepare
- Answer aloud and timed: What are the common challenges you face when implementing backend APIs, and how do you resolve them?
- Answer aloud and timed: How do you ensure your code is secure and optimized for performance?
Conversations with Team Leads
reportedDiscuss team dynamics and long-term professional development.
What to demonstrate
- Discuss team dynamics and long-term professional development
- Depth in Backend Development
How to prepare
- Answer aloud and timed: Can you explain how you handle concurrency and data consistency in your backend systems?
- Answer aloud and timed: How would you design a system to handle a high volume of concurrent messages?
PracHub editorial advice for the preparation topics above.
Prepare your projects
Be ready to discuss your past projects in detail. Know the "why" behind your technical decisions, such as why you chose a specific database or why you structured your API the way you did.
Practice whiteboarding
Even if the interview is remote, be prepared to talk through your design and logic clearly. Use a structured approach to explain your system architecture.
Be honest about your limits
If you don’t know an answer, it is better to explain your logical approach to finding the answer than to guess. Interviewers value transparency and problem-solving skills over memorization.
Engage the interviewer
Treat the interview as a conversation, not an interrogation. Asking thoughtful questions about the team’s current challenges shows genuine interest and engagement.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Can you explain how you handle concurrency and data consistency in your backend systems?
Can you explain how you handle concurrency and data consistency in your backend systems?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- 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?
How do you structure a system to ensure it remains maintainable as it grows in complexity?
How do you structure a system to ensure it remains maintainable as it grows in complexity?
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Collapse a redelivered event batch into per-aggregate high-water marks
You drain a batch of up to 5,000,000 events, each (aggregate_id BIGINT, aggregate_version INT, event_type, payload). The log guarantees order within one aggregate only; the batch merges 64 partitions, and a relay failover has redelivered a range, so an older version for an aggregate can appear after a newer one. Given a map of last_applied_version per aggregate, produce the events worth applying, at most one per (aggregate_id, version), plus the count discarded. Target O(n) time. State the memory for 2,000,000 distinct aggregates and what you do when it does not fit.
Approach
- One pass, one hash map from aggregate_id to the highest version kept, and a discard counter. An event whose version is at or below last_applied_version for its aggregate is dropped without further work, which is the whole reason the event carries its version rather than a delta. O(n) expected time, O(d) space in distinct aggregates.
- Keep the maximum, never the last occurrence. The redelivered range means the final appearance of an aggregate in the batch can be an older version than one seen earlier in the same batch, so last-wins applies stale state over newer state and the projection regresses with no error anywhere.
- Cost the memory instead of calling it large: an 8-byte key plus a 4-byte version is 12 bytes of payload, and an open-addressed table held at a 0.7 load factor costs roughly 17 bytes per entry before per-slot metadata, so 2,000,000 aggregates is tens of megabytes in a native layout and several times that in a runtime that boxes both key and value.
- If the distinct set exceeds memory, partition on hash(aggregate_id) mod P and reduce each partition independently. Every event for one aggregate hashes to the same partition, so the per-partition result is exact and the merge is concatenation rather than a second reduction.
Follow-up
- The payload is a patch rather than a snapshot, so applying only the highest version loses the intermediate changes. What changes in your reduction?
- How do you detect that version 7 arrived while version 6 was never delivered, and what should the consumer do about the gap?
How do you approach database schema design for high-traffic messaging applications?
How do you approach database schema design for high-traffic messaging applications?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
Replace offset paging on the resource feed with keyset
resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.
Approach
- Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
- Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
- Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
- Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.
Follow-up
- The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
- Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?
Can you walk me through the process of building a web service from scratch?
Can you walk me through the process of building a web service from scratch?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
What are the common challenges you face when implementing backend APIs, and how do you resolve them?
What are the common challenges you face when implementing backend APIs, and how do you resolve them?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How do you ensure your code is secure and optimized for performance?
How do you ensure your code is secure and optimized for performance?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How would you design a system to handle a high volume of concurrent messages?
How would you design a system to handle a high volume of concurrent messages?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Can you walk me through the trade-offs between different database architectures for our specific use cases?
Can you walk me through the trade-offs between different database architectures for our specific use cases?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Can you describe a scenario where you had to design a component from the ground up?
Can you describe a scenario where you had to design a component from the ground up?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
How do you approach error handling and system recovery in a distributed environment?
How do you approach error handling and system recovery in a distributed environment?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
One customer endpoint stalls deliveries to every other destination
The egress service delivers about 1.5k webhooks/second across 40,000 destinations, with a per-destination concurrency cap of 4 and a 10-second connect-plus-read timeout. Throughput falls to 300/second, queue depth climbs, and p99 delivery latency for unaffected destinations goes from 200 ms to minutes, while the error rate barely moves. One tenant holds 900 destination rows whose URLs share a hostname that now answers in 9.5 seconds. Explain the mechanism with the arithmetic, then give the containment in the order you would apply it.
Approach
- Look at saturation before errors. A flat error rate with collapsing throughput says nothing is failing, things are waiting, so the first signal to pull is in-flight request count or pool wait time rather than the error counter. This is the distinction that decides the whole investigation.
- Group in-flight work by resolved host, not by destination id. The cap is keyed per destination row, so 900 rows sharing one hostname buy 3,600 concurrent slots against a single host, each held for 9.5 seconds. The bulkhead was never a bulkhead for that host, and grouping by the wrong dimension is why the dashboard looked healthy.
- Do the arithmetic in both directions. Required concurrency is arrival rate times latency, so 1.5k/second at 200 ms needs about 300 in flight, which is entirely consumed by 3,600 slow slots; conversely whatever concurrency is left sustains rate equals concurrency divided by 9.5 seconds, which is the 300/second you are seeing. Matching both numbers is what promotes this from a plausible story to the mechanism.
- Explain why the circuit breaker never helped. It opens on consecutive failures, and a 9.5-second response inside a 10-second timeout is a success. Slow is not failing, so an error-rate breaker cannot see this; you need a slow-call ratio, a deadline propagated from the caller's remaining budget, or a concurrency limiter.
Follow-up
- The host recovers to 80 ms. How long does the queue take to drain, and what does the drain do to the recovered host?
- Where should the 10-second timeout number actually come from?
Built from the rounds and topics WATI candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the WATI loop
- Write out the reported sequence: Initial Screening, Technical Rounds, Conversations with Team Leads.
- 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.
02Work Backend Development
- Spend the session on Backend Development, which WATI candidates report being tested on.
- Write one worked example in Backend Development and time yourself on it.
Deliverable: One timed worked example in Backend Development.
03Work System Design
- Spend the session on System Design, which WATI 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.
04Work Coding / Build from Scratch
- Spend the session on Coding / Build from Scratch, which WATI candidates report being tested on.
- Write one worked example in Coding / Build from Scratch and time yourself on it.
Deliverable: One timed worked example in Coding / Build from Scratch.
05Answer out loud: Technical & Backend Development
- Answer aloud, timed: Can you walk me through the process of building a web service from scratch?
- Answer aloud, timed: How do you approach database schema design for high-traffic messaging applications?
Deliverable: Spoken answers to 2 reported Technical & Backend Development question(s), under time.
06Answer out loud: System Design & Architecture
- Answer aloud, timed: How would you design a system to handle a high volume of concurrent messages?
- Answer aloud, timed: Can you walk me through the trade-offs between different database architectures for our specific use cases?
Deliverable: Spoken answers to 2 reported System Design & Architecture question(s), under time.
07Answer out loud: Behavioral & Problem-Solving
- Answer aloud, timed: Can you describe a difficult technical problem you solved in a past project and the steps you took to overcome it?
- Answer aloud, timed: How do you handle disagreements on technical approaches within your engineering team?
Deliverable: Spoken answers to 2 reported Behavioral & Problem-Solving question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Can you describe a difficult technical problem you solved in a past project and the steps you took to overcome
Can you describe a difficult technical problem you solved in a past project and the steps you took to overcome it?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 disagreements on technical approaches within your engineering team?
How do you handle disagreements on technical approaches within your engineering team?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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?
What is your process for learning new technologies or frameworks when a project requires them?
What is your process for learning new technologies or frameworks when a project requires them?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 balance the need for rapid development with the necessity of writing clean, maintainable code?
How do you balance the need for rapid development with the necessity of writing clean, maintainable code?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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 working at WATI, and how do your career goals align with our mission?
Why are you interested in working at WATI, and how do your career goals align with our mission?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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?
- 01
Can you describe a difficult technical problem you solved in a past project and the steps you took to overcome it?
- 02
How do you handle disagreements on technical approaches within your engineering team?
- 03
What is your process for learning new technologies or frameworks when a project requires them?
- 04
How do you balance the need for rapid development with the necessity of writing clean, maintainable code?
How difficult are the technical interviews at WATI?
Candidates generally describe the difficulty as average to challenging. The focus is not on "trick" questions but on testing your ability to solve real-world engineering problems and explain your reasoning clearly.
WATI Software Engineer candidate reports ↗What is the typical timeline for the interview process?
The process is known for being fast and responsive, with many candidates moving from initial screening to a final decision within a few weeks. Communication is generally prompt, and you will typically receive feedback in a timely manner.
WATI Software Engineer candidate reports ↗Does WATI focus heavily on algorithm questions?
While you should be prepared for coding questions, the interviews place equal, if not greater, weight on your project experience, system design skills, and your ability to communicate your technical choices.
WATI Software Engineer candidate reports ↗What is the culture like for engineers at WATI?
The culture is described as collaborative, professional, and supportive. You will be working with experienced professionals who value open communication and constructive feedback.
WATI Software Engineer candidate reports ↗What topics does WATI test in interviews?
WATI interviews most often cover Interview Process Management, Candidate Experience Optimization, Stakeholder Management, Customer Success (CS), and Backend Development. The exact emphasis depends on the specific role you apply for.
WATI Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01WATI Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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