lytra Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at lytra, you are tasked with solving complex technical challenges that sit at the intersection of software architecture and specialized hardware systems. This role is critical to the company’s mission, requiring you to build robust, scalable solutions that directly impact the performance and reliability of lytra products. You will often work closely with cross-functional teams, bridging the gap between theoretical software models and real-world application. The environment at lytra is one that values directness and practical problem-solving. You should expect to engage in work that requires both high-level system design and low-level code implementation. Whether you are optimizing image processing pipelines or architecting new features, your contribution will be instrumental in driving the company's technical roadmap forward.

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

Focus areas

• C++
• Problem solving
• Basic algorithms

The lytra interview process

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

Phone Screen

Initial call with a recruiter to discuss your background and interest in the company.

What to demonstrate

• Initial call with a recruiter to discuss your background and interest in the company
• Depth in 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 Assessments

Includes shared-interface coding sessions or in-depth technical phone calls with engineers.

What to demonstrate

• Includes shared-interface coding sessions or in-depth technical phone calls with engineers
• Depth in C++

How to prepare

• Answer aloud and timed: How would you optimize this specific data processing function for performance?
• Answer aloud and timed: How would you prevent this lens from fogging up? (You may be asked to analyze a diagram).

Onsite Interview

Meet with multiple team members to discuss your technical skills and project experience.

What to demonstrate

• Meet with multiple team members to discuss your technical skills and project experience
• Depth in C++

How to prepare

• Answer aloud and timed: Describe your approach to architecting a system that handles high-frequency data inputs.
• Answer aloud and timed: How do you balance resource constraints when designing software for specialized hardware?

Where candidates lose points

Prepare your stories

Use the STAR method (Situation, Task, Action, Result) to structure your answers regarding past projects.

Be ready to draw

Since you may face whiteboarding or diagramming tasks, practice explaining your architecture visually.

Be direct

The team at lytra appreciates concise, honest answers. Do not hesitate to admit if you don't know something, but follow it up with how you would find the answer.

Questions & practice

Read a block of C++ code and determine the output.

Medium · Technical Proficiency and Coding

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?

Develop a solution for an algorithm question involving character pointers (char*) and image data.

Medium · Technical Proficiency and Coding

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?

How would you optimize this specific data processing function for performance?

Medium · Technical Proficiency and Coding

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 the update path that detects a concurrent edit

Medium · optimistic concurrency · transactional outbox · audit history

resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.

Approach

1. One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
2. Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
3. State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
4. Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.

Follow-up

• A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
• Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?

Keep soft-deleted accounts from blocking re-registration

Easy · soft delete · unique constraints · engine differences

app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.

Approach

1. Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
2. Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
3. For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
4. State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.

Follow-up

• A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
• How do you honour an erasure request while resource_revision.actor_user_id still references this table?

How would you prevent this lens from fogging up? (You may be asked to analyze a diagram).

Medium · System Design and Problem Solving

Approach

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

Follow-up

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

Describe your approach to architecting a system that handles high-frequency data inputs.

Medium · System Design and Problem Solving

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 balance resource constraints when designing software for specialized hardware?

Medium · System Design and Problem Solving

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?

One log partition stops advancing while the others drain

Easy · poison message · head-of-line blocking · consumer lag

Search results for a subset of tenants are hours stale; the rest are current. The projection consumer reports lag of zero on 15 of 16 partitions and 400,000 on one. Its error rate is flat and its CPU is idle. outbox_event has no pending rows older than a second, so the relay has published everything it holds. Identify the mechanism, give the ordered checks, and state what you do in the first ten minutes versus what you change permanently.

Approach

1. Read the lag distribution first. A slow consumer lags everywhere; zero on fifteen partitions and 400,000 on one is not throughput. Idle CPU on the stuck partition means the consumer is not advancing its offset at all, which points at one message it cannot get past rather than at a rate problem.
2. Exonerate the producer before touching the consumer. No pending outbox rows older than a second means the relay published, so the event exists in the log. This separates never sent from sent and never applied, which are different code paths and usually different owners.
3. Read the message at the stuck offset and the handler's log lines for its event_id. A flat error rate with no progress has two explanations and you must distinguish them: the handler is throwing and the retry loop is swallowing it, or the handler is blocking on something and never returning. Idle CPU with no error lines favours the second.
4. Mitigate before diagnosing further. Move the offending event to a dead-letter store and commit the offset past it. Adding consumers does nothing here, because a partition is consumed by exactly one member of the group, and the blast radius is every aggregate hashed to that partition, not only the aggregate that produced the bad event.

Follow-up

• The dead-lettered event carried aggregate_version 7 and the projection had applied 6. What must the replay do differently if 8 and 9 landed in the meantime?
• How do you show staleness to the user while the partition is behind, given the API already returns the projection's watermark?

Suggested practice checklist

Built from the rounds and topics lytra candidates report.

Day 1 — Map the lytra loop

• Write out the reported sequence: Phone Screen, Technical Assessments, Onsite Interview.
• 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 C++

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

Deliverable: One timed worked example in C++.

Day 3 — Work Problem solving

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

Deliverable: One timed worked example in Problem solving.

Day 4 — Work Basic algorithms

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

Deliverable: One timed worked example in Basic algorithms.

Day 5 — Answer out loud: Technical Proficiency and Coding

• Answer aloud, timed: Read a block of C++ code and determine the output.
• Answer aloud, timed: Develop a solution for an algorithm question involving character pointers (char*) and image data.

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

Day 6 — Answer out loud: System Design and Problem Solving

• Answer aloud, timed: How would you prevent this lens from fogging up? (You may be asked to analyze a diagram).
• Answer aloud, timed: Describe your approach to architecting a system that handles high-frequency data inputs.

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

Day 7 — Answer out loud: Behavioral and Background

• Answer aloud, timed: Why did you have such short-term positions in your previous roles?
• Answer aloud, timed: Can you walk us through a previous project and explain your specific contribution?

Deliverable: Spoken answers to 2 reported Behavioral and Background question(s), under time.

Behavioural preparation

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

Why did you have such short-term positions in your previous roles?

Medium · Behavioral and Background

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?

Can you walk us through a previous project and explain your specific contribution?

Medium · Behavioral and Background

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 qualify for this position, and why is lytra the right fit for your career?

Medium · Behavioral and Background

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?