Invisible Agency Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at Invisible Agency, you play a pivotal role in shaping the technological landscape of the company. This position is integral to developing innovative solutions that meet the dynamic needs of our clients. Your work will directly influence the performance and scalability of our applications, ensuring a seamless experience for users. You will collaborate with cross-functional teams to design, implement, and maintain systems that are not only efficient but also robust against the challenges of a rapidly evolving digital environment. In this role, you will engage with complex problem spaces that require both technical prowess and creative thinking. From building scalable APIs to implementing sophisticated algorithms, your contributions will be vital in enhancing our platform's capabilities.

This guide is scoped to a Software Engineer candidate at Invisible Agency.

Focus areas

• OpenID Connect (OIDC)
• Data Structures and Algorithms (DSA)
• Coding Exercises / Implementation

The Invisible Agency interview process

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

Coding Challenge

Initial round to evaluate technical skills under pressure through a coding challenge.

What to demonstrate

• Initial round to evaluate technical skills under pressure through a coding challenge
• Depth in OpenID Connect (OIDC)

How to prepare

• Answer aloud and timed: What is the difference between a stack and a queue?
• Answer aloud and timed: Explain how a hash table works and provide a use case.

System Design Discussion

Subsequent round focusing on system design discussions to assess design capabilities.

What to demonstrate

• Subsequent round focusing on system design discussions to assess design capabilities
• Depth in OpenID Connect (OIDC)

How to prepare

• Answer aloud and timed: Describe the concept of object-oriented programming and its principles.
• Answer aloud and timed: How would you optimize a slow-running SQL query?

Behavioral Interviews

Interviews with team members or managers to evaluate interpersonal skills and teamwork.

What to demonstrate

• Interviews with team members or managers to evaluate interpersonal skills and teamwork
• Depth in OpenID Connect (OIDC)

How to prepare

• Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
• Re-read the description of the behavioral interviews above and write down what you would ask to confirm before it.

Where candidates lose points

Practice Coding

Regularly practice coding problems on platforms like LeetCode or HackerRank to sharpen your skills.

Understand System Design

Familiarize yourself with system design principles and be prepared to discuss your design choices during interviews.

Showcase Projects

Highlight relevant projects in your portfolio that demonstrate your technical skills and problem-solving abilities.

Be Prepared to Discuss Failures

Reflect on past challenges or failures and how you learned from them; this can provide valuable insights into your character.

Questions & practice

Explain how a hash table works and provide a use case.

Medium · Technical / Domain Questions

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 would you approach a project with ambiguous requirements?

Medium · Problem-Solving / Case Studies

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 function to find the longest substring without repeating characters.

Medium · Coding / Algorithms

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?

Implement a binary search algorithm and explain its efficiency.

Medium · Coding / Algorithms

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?

Given a list of numbers, write a function to find all unique pairs that sum to a specific target.

Medium · Coding / Algorithms

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 would you approach solving a problem using dynamic programming?

Medium · Coding / Algorithms

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 would you optimize a slow-running SQL query?

Medium · Technical / Domain Questions

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?

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?

What is the difference between a stack and a queue?

Medium · Technical / Domain Questions

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?

Describe the concept of object-oriented programming and its principles.

Medium · Technical / Domain Questions

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?

What are some common design patterns you have used in your projects?

Medium · Technical / Domain Questions

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?

Design a URL shortening service. What components would you include?

Medium · System Design / 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 would you approach scaling a web application to handle millions of users?

Medium · System Design / 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?

Discuss the trade-offs of using microservices versus a monolithic architecture.

Medium · System Design / 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?

What considerations would you make for ensuring data consistency in a distributed system?

Medium · System Design / 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 would you design an API for a e-commerce platform?

Medium · System Design / 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?

Given a dataset, how would you identify trends or anomalies?

Medium · Problem-Solving / Case Studies

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?

If a client’s application is experiencing performance issues, what steps would you take to diagnose the proble

Medium · Problem-Solving / Case Studies

If a client’s application is experiencing performance issues, what steps would you take to diagnose the problem?

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?

Exports duplicate a row range about once a week

Hard · leases · clock skew · idempotency

Roughly once a week an export writes a file containing a duplicated range of rows. The affected job_run rows show attempt = 1, status = succeeded, one started_at, and a lease_owner naming a different host from the one whose logs show the job starting. Leases last 30 seconds and are heartbeated every 10 from inside the handler; lease_expires_at is computed on the worker and compared against the database's now(). Find the mechanism, and give a fix that holds even if you cannot fix the clocks.

Approach

1. Start from the fact that eliminates the obvious answer. attempt = 1 means no retry was recorded, so this is not a re-run after failure; two workers ran the same row concurrently and the takeover path never touched the counter. lease_owner naming a host other than the one that started the job is the same statement from the other side.
2. Enumerate the mechanisms that cause a premature takeover, then find the signal that separates them. Either the lease genuinely expired because the heartbeat did not fire, which is what happens when the heartbeat runs on the handler's own thread and the handler makes a long blocking call, or it only appeared expired because two clocks disagree, since lease_expires_at is written from the worker's clock and evaluated against the database's. The discriminator is the distribution: incidents clustered on the longest exports indict the heartbeat, incidents clustered on one host indict skew. Measure both, and measure each host's offset against the database directly.
3. Read the reclaim query precisely. In PostgreSQL now() is transaction start time, not statement time, so a reclaimer holding a long transaction compares against an older timestamp than expected; clock_timestamp() is the statement-time function. This is worth ruling in or out before you redesign anything, because it changes which rows look expired.
4. Remove the second clock rather than trying to synchronise it. Issue and extend the lease in the database, with lease_expires_at = now() + interval '30 seconds' in both the claim and the heartbeat, so exactly one clock is ever compared and worker skew stops mattering to this predicate.

Follow-up

• The displaced worker has already streamed half the file to object storage. What makes that side effect safe to repeat?
• You now count takeovers. What alert fires on that counter, and at what threshold?

Suggested practice checklist

Built from the rounds and topics Invisible Agency candidates report.

Day 1 — Map the Invisible Agency loop

• Write out the reported sequence: Coding Challenge, System Design Discussion, Behavioral Interviews.
• 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 OpenID Connect (OIDC)

• Spend the session on OpenID Connect (OIDC), which Invisible Agency candidates report being tested on.
• Write one worked example in OpenID Connect (OIDC) and time yourself on it.

Deliverable: One timed worked example in OpenID Connect (OIDC).

Day 3 — Work Data Structures and Algorithms (DSA)

• Spend the session on Data Structures and Algorithms (DSA), which Invisible Agency candidates report being tested on.
• Write one worked example in Data Structures and Algorithms (DSA) and time yourself on it.

Deliverable: One timed worked example in Data Structures and Algorithms (DSA).

Day 4 — Work Coding Exercises / Implementation

• Spend the session on Coding Exercises / Implementation, which Invisible Agency candidates report being tested on.
• Write one worked example in Coding Exercises / Implementation and time yourself on it.

Deliverable: One timed worked example in Coding Exercises / Implementation.

Day 5 — Answer out loud: Technical / Domain Questions

• Answer aloud, timed: What is the difference between a stack and a queue?
• Answer aloud, timed: Explain how a hash table works and provide a use case.

Deliverable: Spoken answers to 2 reported Technical / Domain Questions question(s), under time.

Day 6 — Answer out loud: System Design / Architecture

• Answer aloud, timed: Design a URL shortening service. What components would you include?
• Answer aloud, timed: How would you approach scaling a web application to handle millions of users?

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

Day 7 — Answer out loud: Behavioral / Leadership

• Answer aloud, timed: Describe a challenging project you worked on and how you overcame obstacles.
• Answer aloud, timed: How do you prioritize tasks when facing tight deadlines?

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

Behavioural preparation

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

Describe a challenging project you worked on and how you overcame obstacles.

Medium · Behavioral / Leadership

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 prioritize tasks when facing tight deadlines?

Medium · Behavioral / Leadership

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 give an example of a conflict within a team and how you resolved it?

Medium · Behavioral / Leadership

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?

Discuss a time when you had to adapt to significant changes in a project.

Medium · Behavioral / Leadership

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 ensure effective communication within a team?

Medium · Behavioral / Leadership

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?

Provide an example of a time when you had to learn a new technology quickly to complete a project.

Medium · Problem-Solving / Case Studies

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?