Flexe Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at Flexe, you are at the core of transforming the logistics and supply chain industry. You aren't just writing code; you are building the digital infrastructure that enables flexible warehousing and fulfillment at scale. Your work directly impacts how businesses manage inventory and reach their customers, necessitating a blend of technical precision and an understanding of complex logistics workflows. You will be expected to tackle challenges that go beyond simple CRUD operations. The role involves designing systems that handle real-time data, optimize inventory distribution, and provide reliable, scalable solutions for our partners. You will collaborate closely with product managers and operations teams to solve real-world problems, making your contribution both highly visible and strategically vital to the company’s mission.

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

Focus areas

• System Design
• Coding Interviews (Practice-Driven Coding Questions)
• Algorithms & Problem Solving

The Flexe interview process

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

Recruiter Screen

Initial discussion with a recruiter about your background and interest in the position.

What to demonstrate

• Initial discussion with a recruiter about your background and interest in the position
• Depth in System Design

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 Assessment

Assessment to evaluate your technical skills, typically involving coding tasks.

What to demonstrate

• Assessment to evaluate your technical skills, typically involving coding tasks
• Depth in System Design

How to prepare

• Answer aloud and timed: How would you structure a unit-test suite for a core logistics function to ensure reliability?
• Answer aloud and timed: Explain the trade-offs between different data structures for a high-frequency lookup scenario.

Virtual or Onsite Rounds

Series of interviews that may include coding, system design, and behavioral assessments.

What to demonstrate

• Series of interviews that may include coding, system design, and behavioral assessments
• Depth in System Design

How to prepare

• Answer aloud and timed: Given a set of warehouse constraints, design an algorithm to optimize the placement of goods.
• Answer aloud and timed: How would you design a distributed system to track inventory across multiple geographic locations?

Where candidates lose points

Bring your own environment

For coding rounds, we often allow you to use your own IDE. This is intended to make you more comfortable, so take advantage of it to showcase your best work.

Communicate your thought process

We are more interested in how you arrive at a solution than the solution itself. Talk through your assumptions, trade-offs, and potential pitfalls as you work.

Ask meaningful questions

Use the time at the end of your interviews to ask about the team’s current technical challenges or the company’s long-term product roadmap.

Be honest about your skills

If you are unfamiliar with a specific tool or technology mentioned, it is better to explain your experience with similar technologies and your willingness to learn than to guess.

Questions & practice

Write a function to process a stream of inventory data and identify specific patterns or anomalies.

Medium · Coding and 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 solution for string manipulation that handles complex grouping requirements.

Medium · Coding and 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 structure a unit-test suite for a core logistics function to ensure reliability?

Medium · Coding and 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?

Explain the trade-offs between different data structures for a high-frequency lookup scenario.

Medium · Coding and 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?

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?

Hold a per-tenant active cap against concurrent creates

Hard · write skew · isolation levels · constraints

A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.

Approach

1. Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
2. Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
3. Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
4. State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.

Follow-up

• A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
• The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?

Given a set of warehouse constraints, design an algorithm to optimize the placement of goods.

Medium · Coding and Algorithms

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 a distributed system to track inventory across multiple geographic locations?

Medium · System Design

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 the architecture for a service that needs to handle high bursts of traffic during peak retail seasons

Medium · System Design

Describe the architecture for a service that needs to handle high bursts of traffic during peak retail seasons.

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 are the trade-offs between a monolithic architecture and microservices in the context of our supply chain

Medium · System Design

What are the trade-offs between a monolithic architecture and microservices in the context of our supply chain platform?

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 ensure data consistency in a system where multiple nodes update inventory status simultaneously?

Medium · System Design

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?

p99 jumped on one listing filter while p50 stayed flat

Medium · query planning · composite index · percentiles

After a release that added an owner_user_id filter to the resource listing, p99 rose from 90 ms to 1.9 s while p50 stayed at 40 ms. Traffic and row counts are unchanged. resource carries the index (tenant_id, status, updated_at DESC, resource_id DESC). The new query filters tenant_id and owner_user_id, orders by updated_at DESC, resource_id DESC, and takes 20 rows. On PostgreSQL, explain the shape of the regression, prove it from a query plan, and give the index you would add.

Approach

1. Start from the shape. A flat p50 with a moved p99 means a subset of requests changed cost, not all of them, so the first job is naming the subset. Bucket the endpoint's latency by the tenant's row count; the natural hypothesis is that large tenants are a small share of requests and all of the tail.
2. Get the plan for the new query on a large tenant with EXPLAIN (ANALYZE, BUFFERS). Expect an index scan over the tenant's range, a filter discarding most of it, then a Sort feeding the Limit, possibly reporting Sort Method: external merge Disk. Read actual rows on the scan node, not estimated.
3. Explain why the existing index cannot serve it. A composite B-tree is seekable only as a left prefix, and with no equality predicate on status the scan cannot treat updated_at as an ordering, because rows in the tenant's range are ordered by status first. Everything matching must be read and sorted before LIMIT 20 can apply, so a tenant with 400,000 rows pays 400,000 rows to return 20.
4. Add (tenant_id, owner_user_id, updated_at DESC, resource_id DESC). Equality on the first two columns leaves the index ordered by updated_at within that pair, so the plan becomes an index scan that stops after 20 rows with no Sort node. PostgreSQL can scan a B-tree backwards, so the DESC markers matter only if the two sort columns ever disagree in direction; keeping them explicit documents the order the keyset cursor depends on.

Follow-up

• The endpoint paginates with OFFSET. What does page 500 cost with your index, and what does the keyset version cost?
• How would you have caught this before release, given that a 10,000-row seed database produces the same plan shape at an unnoticeable cost?

Suggested practice checklist

Built from the rounds and topics Flexe candidates report.

Day 1 — Map the Flexe loop

• Write out the reported sequence: Recruiter Screen, Technical Assessment, Virtual or Onsite Rounds.
• 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 System Design

• Spend the session on System Design, which Flexe 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.

Day 3 — Work Coding Interviews (Practice-Driven Coding Questions)

• Spend the session on Coding Interviews (Practice-Driven Coding Questions), which Flexe candidates report being tested on.
• Write one worked example in Coding Interviews (Practice-Driven Coding Questions) and time yourself on it.

Deliverable: One timed worked example in Coding Interviews (Practice-Driven Coding Questions).

Day 4 — Work Algorithms & Problem Solving

• Spend the session on Algorithms & Problem Solving, which Flexe candidates report being tested on.
• Write one worked example in Algorithms & Problem Solving and time yourself on it.

Deliverable: One timed worked example in Algorithms & Problem Solving.

Day 5 — Answer out loud: Coding and Algorithms

• Answer aloud, timed: Write a function to process a stream of inventory data and identify specific patterns or anomalies.
• Answer aloud, timed: Implement a solution for string manipulation that handles complex grouping requirements.

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

Day 6 — Answer out loud: System Design

• Answer aloud, timed: How would you design a distributed system to track inventory across multiple geographic locations?
• Answer aloud, timed: Describe the architecture for a service that needs to handle high bursts of traffic during peak retail seasons.

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

Day 7 — Answer out loud: Behavioral and Values

• Answer aloud, timed: Tell me about a time you had to pivot your technical approach due to shifting business requirements.
• Answer aloud, timed: Describe a situation where you had to work with a cross-functional team to solve a complex problem.

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

Behavioural preparation

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

Tell me about a time you had to pivot your technical approach due to shifting business requirements.

Medium · Behavioral and Values

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?

Describe a situation where you had to work with a cross-functional team to solve a complex problem.

Medium · Behavioral and Values

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 handle technical debt when there is pressure to deliver new features quickly?

Medium · Behavioral and Values

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 provide an example of how you have mentored a teammate or improved a team process?

Medium · Behavioral and Values

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?