cswork / libraryOpen practice workspace

Interview guides · fast-growing technology

fast-growing technology Software Engineer Interview Guide

fast-growing technology Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at fast-growing technology, you are at the forefront of building the digital infrastructure for physical AI. This role is critical to the company’s mission, as you will be responsible for the design, development, and optimization of high-performance software that powers complex, real-world systems. You will work on projects that directly impact the reliability and scalability of technologies used in sensitive and demanding environments, such as uncrewed aerial systems and remotely operated systems. This position is inherently challenging, requiring a blend of deep technical expertise and a pragmatic approach to system architecture. You will be expected to translate high-level requirements into robust, maintainable code, often working across international teams to ensure consistency and performance.

This guide is scoped to a Software Engineer candidate at fast-growing technology.

Focus areas

  • Modern C++
  • High-Performance Software
  • Scalability

The fast-growing technology interview process

fast-growing technology candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screen

Initial discussion to align on your background and interest in the role.

What to demonstrate

  • Initial discussion to align on your background and interest in the role
  • Depth in Modern C++

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 Lead Conversation

Discussion with a technical lead or manager to assess technical fit.

What to demonstrate

  • Discussion with a technical lead or manager to assess technical fit
  • Depth in Modern C++

How to prepare

  • Answer aloud and timed: What are the advantages and drawbacks of using smart pointers versus raw pointers in your current projects?
  • Answer aloud and timed: How do you approach debugging a memory leak in a large-scale, multi-threaded codebase?

Technical Assessment

Rigorous evaluation that may include a coding screen or a take-home project.

What to demonstrate

  • Rigorous evaluation that may include a coding screen or a take-home project
  • Depth in Modern C++

How to prepare

  • Answer aloud and timed: Describe your process for optimizing a piece of code that is identified as a performance bottleneck.
  • Answer aloud and timed: How would you design a service-oriented architecture that requires low-latency communication between components?

Onsite Loop

Comprehensive onsite interviews covering technical deep dives, system design, and behavioral alignment.

What to demonstrate

  • Comprehensive onsite interviews covering technical deep dives, system design, and behavioral alignment
  • Depth in Modern C++

How to prepare

  • Answer aloud and timed: What considerations do you prioritize when designing a system that must be both highly reliable and secure?
  • Answer aloud and timed: How do you handle data consistency in a distributed system where network partitions might occur?

Where candidates lose points

Structure your answers

Use the STAR method (Situation, Task, Action, Result) for behavioral questions to keep your responses clear and impact-focused.

Explain your reasoning

During coding or design sessions, think out loud. Interviewers care as much about your problem-solving process as they do about the final answer.

Focus on C++ fundamentals

Don't just memorize syntax; understand the "why" behind memory management and performance trade-offs in C++.

Clarify requirements

If a technical question seems ambiguous, ask clarifying questions before diving into a solution. This is a sign of a thoughtful engineer.

Questions & practice

How do you manage memory allocation in a high-performance C++ application to avoid latency?

Medium · Technical and C++ Proficiency

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?

Can you explain the difference between stack and heap memory in the context of real-time systems?

Medium · Technical and C++ Proficiency

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

What are the advantages and drawbacks of using smart pointers versus raw pointers in your current projects?

Medium · Technical and C++ Proficiency

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?

Replace offset paging on the resource feed with keyset

Easy · keyset pagination · composite index · sort order

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

  1. 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.
  2. 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.
  3. 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.
  4. 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?

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?

Describe your process for optimizing a piece of code that is identified as a performance bottleneck.

Medium · Technical and C++ Proficiency

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 design a service-oriented architecture that requires low-latency communication between component

Medium · System Design and Architecture

How would you design a service-oriented architecture that requires low-latency communication between components?

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

What considerations do you prioritize when designing a system that must be both highly reliable and secure?

Medium · System Design and Architecture

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

How do you handle data consistency in a distributed system where network partitions might occur?

Medium · System Design and 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?

Explain the trade-offs between using different message broker paradigms for high-throughput data streams.

Medium · System Design and Architecture

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

How do you ensure that your software architecture remains maintainable as new features are added over time?

Medium · System Design and Architecture

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

How do you approach debugging a memory leak in a large-scale, multi-threaded codebase?

Medium · Technical and C++ Proficiency

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 fast-growing technology candidates report.

Day 1 — Map the fast-growing technology loop

  • Write out the reported sequence: Recruiter Screen, Technical Lead Conversation, Technical Assessment, 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 4 reported rounds, with the weakest marked.

Day 2 — Work Modern C++

  • Spend the session on Modern C++, which fast-growing technology candidates report being tested on.
  • Write one worked example in Modern C++ and time yourself on it.

Deliverable: One timed worked example in Modern C++.

Day 3 — Work High-Performance Software

  • Spend the session on High-Performance Software, which fast-growing technology candidates report being tested on.
  • Write one worked example in High-Performance Software and time yourself on it.

Deliverable: One timed worked example in High-Performance Software.

Day 4 — Work Scalability

  • Spend the session on Scalability, which fast-growing technology candidates report being tested on.
  • Write one worked example in Scalability and time yourself on it.

Deliverable: One timed worked example in Scalability.

Day 5 — Answer out loud: Technical and C++ Proficiency

  • Answer aloud, timed: How do you manage memory allocation in a high-performance C++ application to avoid latency?
  • Answer aloud, timed: Can you explain the difference between stack and heap memory in the context of real-time systems?

Deliverable: Spoken answers to 2 reported Technical and C++ Proficiency question(s), under time.

Day 6 — Answer out loud: System Design and Architecture

  • Answer aloud, timed: How would you design a service-oriented architecture that requires low-latency communication between components?
  • Answer aloud, timed: What considerations do you prioritize when designing a system that must be both highly reliable and secure?

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

Day 7 — Dry run for fast-growing technology

  • 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.

Behavioural preparation

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

Unblock an engineer without taking the keyboard

Easy · mentoring · leases · at-least-once

A teammate has spent two days on a job handler that occasionally writes duplicate rows. They are certain the queue is delivering twice by mistake. You suspect a lease expiring under a slow handler, so the job is running concurrently with itself. Describe how you have unblocked someone in this position: what you asked before offering a hypothesis, what you showed them rather than told them, and what you left them owning. Then say what you would do if their theory turned out to be the right one.

Approach

  1. Ask before diagnosing, and ask for things answerable from data they already have: the attempt count on the job rows that produced duplicates, the handler's observed duration against its lease expiry, and whether the duplicate rows share a natural key that a unique constraint could have caught.
  2. Teach the shape rather than the answer. A lease cannot distinguish a dead worker from a slow one, so a handler that outruns its lease is running twice by design, and deploys deliver the other half by killing handlers mid-run on every rollout. Both of their candidate theories produce identical duplicate rows, which is why the evidence has to come from timings rather than from argument.
  3. Hand over a checklist they execute: a natural key on every write the handler performs so the second copy collides rather than appends, the record of intent written before any external effect, a lease heartbeat while running, and the metric that shows it working.
  4. Keep ownership with them deliberately. Pair on the first write, then step back; if you finish it yourself you have closed one ticket and left the same person stuck on the next redelivery.

Follow-up

  • How would you distinguish a genuine double-delivery from a lease expiry using only the data already stored?
  • Their handler calls an external endpoint before recording that it did. What do you tell them to change first?

Narrate an outage you owned from page to postmortem

Hard · incident response · blast radius · postmortems

Pick an incident you personally drove, ideally one where writes were affected rather than reads. In six to eight minutes: state the symptom as it first appeared on a dashboard, the blast radius you established before you knew the cause, the mitigation you applied and when, the mechanism you eventually proved, and the follow-up that would prevent a repeat. Bring numbers: error rate, tenants affected, minutes to mitigate, minutes to resolve. If you cannot name what you measured, choose a different incident.

Approach

  1. Open on the signal rather than the cause: which metric at which percentile moved, on which service, at what time, so the listener follows the same evidence you had rather than a conclusion you already reached.
  2. Separate mitigation from diagnosis out loud. State what you did to stop the bleeding (flag off, shed traffic, drain a lease, roll back a deploy) and say plainly that you did it before the mechanism was known, because those are two jobs with different deadlines.
  3. Establish blast radius in countable terms: how many tenants, how many writes, and crucially whether the effect was loss or only delay. An append-only revision table or a pending outbox row means the change survived and the projection was merely behind, which is a repair rather than a data-loss incident.
  4. Prove the mechanism instead of asserting it. Name the trace span that grew, the plan that flipped to a sequential scan, the lease that expired, plus one alternative you ruled out and the signal that stayed flat while you ruled it out.

Follow-up

  • What would you do differently in the first five minutes, given the same dashboard and no more information?
  • Which follow-up action did you deliberately not take, and why was dropping it the right call?

Reverse your own decision and price the reversal

Medium · reversibility · measurement · migrations

Describe a technical decision you made and later reversed. Pick one that cost something: a service you split and merged back, a cache you added and removed, an index you created that pushed the planner onto a worse plan, a projection you rebuilt from scratch. State what you believed when you decided, the measurement that changed your mind, how long the wrong version ran in production, and what the reversal cost in migrations, dual writes, and a deprecation window for callers you did not own.

Approach

  1. State the original rationale without irony, in the version you would still defend given what was known then. If it is not defensible, the story is about carelessness rather than judgement, and a different example serves you better.
  2. Give the measurement that moved with a before and after: the p99 that did not improve, the cache hit rate that sat at 40%, the plan that flipped to a sequential scan once the table passed a size you can name.
  3. Cost the reversal in steps, not adjectives: expand-and-contract deploys, the dual-write window, the callers who had to be notified, the rows already written in the wrong shape that had to be backfilled or abandoned.
  4. Distinguish reversal from rewrite by naming what you kept. Most good reversals preserve the schema or the interface and undo one decision inside it, which is also why they were affordable.

Follow-up

  • What in that decision was irreversible, and did you know it was irreversible when you made it?
  • How did you tell the people who had already built on top of the original decision?