As a Software Engineer at Mouts TI, you act as a primary driver of technical innovation, bridging the gap between complex business requirements and scalable software solutions. Your work is central to the company’s ability to deliver high-quality digital products for a diverse range of clients. You will not just be writing code; you will be architecting systems, ensuring robust performance, and collaborating closely with stakeholders to solve real-world problems. This role demands a high level of versatility. Whether you are working on full-stack development, integrating complex cloud services, or ensuring system reliability through automated testing, your contributions directly influence the success of our client engagements. At Mouts TI, we value engineers who possess a deep curiosity for new technologies and a pragmatic approach to software craftsmanship. You will operate in a dynamic environment where your ability to translate technical concepts into business value is as important as your coding proficiency.
Recruitment Screen
reportedInitial screening to ensure mutual alignment between the candidate and the company.
What to demonstrate
- Initial screening to ensure mutual alignment between the candidate and the company
- Depth in Authentication with JWT
How to prepare
- Answer aloud and timed: How do you approach the design of a RESTful API to ensure it is both scalable and maintainable?
- Answer aloud and timed: Can you explain how you handle authentication and authorization in a distributed system, specifically using JWT?
Technical Assessment
reportedAssessment that tests the candidate's practical development skills through a coding challenge.
What to demonstrate
- Assessment that tests the candidate's practical development skills through a coding challenge
- Depth in Authentication with JWT
How to prepare
- Answer aloud and timed: What are the trade-offs between different database strategies when building a high-traffic CRUD application?
- Answer aloud and timed: How do you implement message queues or service bus architectures to decouple services in a microservices environment?
Discussion with Leadership
reportedFinal discussion with project leadership or clients to evaluate project management and communication skills.
What to demonstrate
- Final discussion with project leadership or clients to evaluate project management and communication skills
- Depth in Authentication with JWT
How to prepare
- Answer aloud and timed: What is your strategy for ensuring high code quality through automated testing in both front-end and back-end environments?
- Answer aloud and timed: Can you describe a time you had to explain a complex technical trade-off to a non-technical stakeholder?
PracHub editorial advice for the preparation topics above.
Prioritize Testing
Never submit a coding challenge without automated tests. It is a non-negotiable indicator of your professional maturity.
Document Your Work
Include a clear README file in your technical submissions explaining your architectural decisions and how to run your application.
Be Transparent About Timelines
If you need more time for a challenge, communicate it early. We value honesty and professional planning.
Focus on the Client
During the final stage, remember that the client is looking for a partner who understands their business goals, not just a coder.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Archive a resource graph without breaking live references or recursing
Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.
Approach
- Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
- Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
- Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
- Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.
Follow-up
- The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
- The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?
Find overlapping job attempts and peak concurrency from lease records
A day of job_run history yields about 50,000,000 attempt records: (job_run_id, job_type, attempt, started_at, finished_at which is NULL when the worker died, lease_expires_at). Leases expire on a clock, so a job that outran its lease ran twice. Produce (a) every job_run_id whose attempts overlapped in wall-clock time and (b) the peak number of simultaneously running attempts per job_type with the minute it occurred. Target O(n log n). State how you treat a NULL finished_at and what clock skew does to your answer.
Approach
- Define the interval before sorting anything: an attempt occupies [started_at, COALESCE(finished_at, lease_expires_at)). finished_at is observed and lease_expires_at is only a promise, so every attempt without a finish contributes an estimate and the whole result is a lower bound on overlap rather than an exact count.
- For peak concurrency, sweep: emit 2n endpoints, sort by (timestamp, kind) with ends ordered before starts at equal timestamps, then walk the sequence maintaining a counter per job_type and record each type's maximum with its timestamp. O(n log n) dominated by the sort, O(n) space, or O(1) extra if the sort is external and the walk streams.
- For overlap detection, do not compare attempts pairwise. A single global sort by (job_run_id, started_at) gives both the grouping and the order; within a group, keep the maximum end seen so far and report an overlap exactly when the next start is less than that running maximum, which is one linear pass after the sort.
- Half-open intervals matter and are easy to get wrong: with closed intervals an attempt ending at the same millisecond another begins reads as concurrency two, and across 50,000,000 records that artefact swamps the real signal.
Follow-up
- A handler is not idempotent and you have found 400 overlapping jobs. Which of them actually caused damage, and what would you query to find out?
- Peak concurrency for one job_type is 4 against a configured cap of 4. Is the cap working, or is the data hiding attempts that never started?
Merge partitioned event streams into one ordered feed with bounded lateness
The read-model service consumes 64 log partitions carrying about 4,000 events per second in total. Each partition is ordered within itself, but partitions drift by up to 30 seconds, and the activity feed must present a tenant's events in occurred_at order. Produce the merge. State its complexity, the buffer it requires in events and in bytes, what happens when one partition is idle, and what you do with an event that arrives after you have already emitted its position. Payloads average 1 KB.
Approach
- Merge with a min-heap over the 64 partition heads keyed on (occurred_at, event_id): O(log P) per event and O(n log P) overall. The tie-break on event_id is what makes the output deterministic when two partitions carry the same millisecond, which matters because the feed is paginated and a non-deterministic order reorders pages under the reader.
- Emitting the heap head is only correct once every partition has produced everything up to that timestamp, so the emit condition is a watermark: the minimum across partitions of the highest occurred_at seen, less the allowed lateness. Events are held until the watermark passes them, which is what turns individually ordered streams into a jointly ordered one.
- Size the buffer from the lateness rather than guessing: 4,000 events per second times 30 seconds is 120,000 buffered events, and at 1 KB each about 120 MB of heap. That number is the real price of the ordering guarantee and belongs in front of whoever asked for it.
- Handle the idle partition explicitly, because it fails the feed rather than corrupting it: a partition with no traffic never advances its own maximum, so the watermark freezes and output stops entirely. Either every partition emits a periodic idle marker carrying the broker's current time, or the watermark falls back to wall clock for a partition silent beyond a threshold.
Follow-up
- The lateness budget is raised to five minutes. What is the new buffer, and what besides memory changes?
- The consumer restarts. Where does it resume from, and what does the feed look like for the first 30 seconds?
Explain why the owner filter ignores the listing index
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
- 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.
- 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.
- 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.
- 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?
Find version gaps and relay lag with window functions
outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.
Approach
- Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
- Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
- Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
- Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.
Follow-up
- Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
- Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?
How do you approach the design of a RESTful API to ensure it is both scalable and maintainable?
How do you approach the design of a RESTful API to ensure it is both scalable and maintainable?
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 explain how you handle authentication and authorization in a distributed system, specifically using JW
Can you explain how you handle authentication and authorization in a distributed system, specifically using JWT?
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?
What are the trade-offs between different database strategies when building a high-traffic CRUD application?
What are the trade-offs between different database strategies when building a high-traffic CRUD application?
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 implement message queues or service bus architectures to decouple services in a microservices envir
How do you implement message queues or service bus architectures to decouple services in a microservices 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?
What is your strategy for ensuring high code quality through automated testing in both front-end and back-end
What is your strategy for ensuring high code quality through automated testing in both front-end and back-end environments?
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?
Describe your process for debugging a critical production issue under tight time constraints.
Describe your process for debugging a critical production issue under tight time constraints.
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- 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?
Built from the rounds and topics Mouts TI candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Mouts TI loop
- Write out the reported sequence: Recruitment Screen, Technical Assessment, Discussion with Leadership.
- 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 Authentication with JWT
- Spend the session on Authentication with JWT, which Mouts TI candidates report being tested on.
- Write one worked example in Authentication with JWT and time yourself on it.
Deliverable: One timed worked example in Authentication with JWT.
03Work CRUD Development
- Spend the session on CRUD Development, which Mouts TI candidates report being tested on.
- Write one worked example in CRUD Development and time yourself on it.
Deliverable: One timed worked example in CRUD Development.
04Work .NET 8
- Spend the session on .NET 8, which Mouts TI candidates report being tested on.
- Write one worked example in .NET 8 and time yourself on it.
Deliverable: One timed worked example in .NET 8.
05Answer out loud: Technical Proficiency and Architecture
- Answer aloud, timed: How do you approach the design of a RESTful API to ensure it is both scalable and maintainable?
- Answer aloud, timed: Can you explain how you handle authentication and authorization in a distributed system, specifically using JWT?
Deliverable: Spoken answers to 2 reported Technical Proficiency and Architecture question(s), under time.
06Answer out loud: Behavioral and Process-Oriented
- Answer aloud, timed: Can you describe a time you had to explain a complex technical trade-off to a non-technical stakeholder?
- Answer aloud, timed: How do you handle situations where you receive conflicting requirements from a client and your internal team?
Deliverable: Spoken answers to 2 reported Behavioral and Process-Oriented question(s), under time.
07Dry run for Mouts TI
- Run one full mock under time, then write down the two questions you most want to ask your interviewers.
Deliverable: A completed timed mock and two questions to ask.
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 time you had to explain a complex technical trade-off to a non-technical stakeholder?
Can you describe a time you had to explain a complex technical trade-off to a non-technical stakeholder?
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 situations where you receive conflicting requirements from a client and your internal team?
How do you handle situations where you receive conflicting requirements from a client and your internal 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?
How do you manage your time when balancing multiple project deliverables?
How do you manage your time when balancing multiple project deliverables?
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 time you had to explain a complex technical trade-off to a non-technical stakeholder?
- 02
How do you handle situations where you receive conflicting requirements from a client and your internal team?
- 03
How do you manage your time when balancing multiple project deliverables?
How long does the entire process usually take?
The process is designed to be efficient; typically, it can move from the first contact to the final interview within a few weeks, depending on your availability and current project cycles.
Mouts TI Software Engineer candidate reports ↗Is the technical challenge performed live or offline?
The process usually includes both an offline technical challenge to assess your ability to build a complete feature and a live coding session to evaluate your real-time problem-solving skills.
Mouts TI Software Engineer candidate reports ↗What is the most common reason candidates do not proceed?
Candidates often struggle when they fail to provide comprehensive test coverage or neglect documentation in their technical submissions. Attention to detail is highly valued here.
Mouts TI Software Engineer candidate reports ↗How does Mouts TI handle feedback?
We strive to be transparent. While we occasionally experience high volumes of applications, our recruiters aim to keep candidates informed at every stage of the process.
Mouts TI Software Engineer candidate reports ↗What topics does Mouts TI test in interviews?
Mouts TI interviews most often cover.NET 8, Authentication with JWT, React (front-end), Data Analysis (General), and CRUD Development. The exact emphasis depends on the specific role you apply for.
Mouts TI 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.
- 01Mouts TI 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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