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Bestow Software Engineer Interview Guide

Bestow Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

A Software Engineer at Bestow plays a vital role in building and enhancing the digital infrastructure that powers the company's innovative life insurance solutions. This position is essential for ensuring the reliability, scalability, and security of products that aim to simplify the insurance process for users. As a Software Engineer, you will be at the forefront of developing features that directly impact customer experience, contributing to the mission of making life insurance accessible and hassle-free. In this role, you will work closely with cross-functional teams, including product managers and designers, to architect, design, and implement solutions that address real-world problems. The complexity of the systems you’ll be involved with offers significant challenges and learning opportunities.

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

Focus areas

  • Technical interviewing / coding assessments
  • SQL (query writing)
  • Golang (Go)

The Bestow interview process

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

Phone Screen

Initial call with a recruiter to assess your background and fit for the role.

What to demonstrate

  • Initial call with a recruiter to assess your background and fit for the role
  • Depth in Technical interviewing / coding assessments

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 Interview

Interview with the hiring manager focusing on technical skills and problem-solving.

What to demonstrate

  • Interview with the hiring manager focusing on technical skills and problem-solving
  • Depth in Technical interviewing / coding assessments

How to prepare

  • Answer aloud and timed: Explain how you would design a RESTful API for a life insurance application.
  • Answer aloud and timed: What is your experience with cloud technologies, and how have you implemented them in past projects?

Coding Assessment

Complete a coding assessment through the Woven platform simulating real-world scenarios.

What to demonstrate

  • Complete a coding assessment through the Woven platform simulating real-world scenarios
  • Depth in Technical interviewing / coding assessments

How to prepare

  • Answer aloud and timed: How do you ensure the security and performance of your applications?
  • Answer aloud and timed: Given a scenario where a life insurance application experiences high latency, how would you investigate and resolve the issue?

Technical Interviews

Series of interviews including coding challenges, system design discussions, and behavioral interviews.

What to demonstrate

  • Series of interviews including coding challenges, system design discussions, and behavioral interviews
  • Depth in Technical interviewing / coding assessments

How to prepare

  • Answer aloud and timed: Walk us through your thought process in designing a feature for our existing platform.
  • Answer aloud and timed: How would you approach refactoring a legacy codebase to improve maintainability?

Where candidates lose points

Practice Coding Problems

Regularly solve coding challenges on platforms like LeetCode or HackerRank to sharpen your skills.

Understand Bestow's Mission

Familiarize yourself with the company’s goals and how your work can contribute to improving the insurance experience for users.

Prepare Questions

Have insightful questions ready for your interviewers to demonstrate your interest and engagement with the role and company.

Stay Calm and Confident

Interviews can be stressful, but maintaining composure and confidence will help you perform your best.

Questions & practice

Write a function to find the longest common substring in two strings.

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, find two numbers that add up 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 implement a caching mechanism to improve application performance?

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?

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?

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?

What programming languages are you proficient in, and can you provide examples of projects where you used them

Medium · Technical / Domain Questions

What programming languages are you proficient in, and can you provide examples of projects where you used them?

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 a challenging technical problem you faced and how you approached solving it.

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?

Explain how you would design a RESTful API for a life insurance application.

Medium · Technical / Domain Questions

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 the security and performance of your applications?

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?

Given a scenario where a life insurance application experiences high latency, how would you investigate and re

Medium · Problem-Solving / Case Studies

Given a scenario where a life insurance application experiences high latency, how would you investigate and resolve the issue?

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?

Walk us through your thought process in designing a feature for our existing platform.

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?

How would you approach refactoring a legacy codebase to improve maintainability?

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?

Edge instances grow 400 MB per hour until the nightly restart

Hard · memory leak · heap analysis · metric cardinality

Edge API instances start at 700 MB resident and grow about 400 MB/hour; a nightly rolling restart has hidden it for weeks. Growth continues unchanged when request rate halves overnight, p99 degrades in the last hours before an instance is recycled, and heap used immediately after a forced full GC rises monotonically. The service holds no product state. Name the discriminating measurement that separates the plausible causes, give the most likely cause, and give the fix and how you would verify it.

Approach

  1. Separate resident memory from live heap first, because they fail differently. Resident size can grow from fragmentation, native buffers or thread stacks while the heap is flat; heap used after a full GC rising monotonically is the measurement that says objects are reachable and not being released. You already have it, so this is retention, not fragmentation, and that closes off half the candidate list.
  2. Use the rate's independence from traffic as the discriminator. Growth that continues at half the request rate rules out per-request objects that are merely slow to collect and points at a structure that grows with distinct values observed rather than with call volume. Write the candidates that have that property: a metrics registry keyed on a high-cardinality label, an unevicted cache, an interner, a per-key lock map.
  3. Take two heap snapshots an hour apart and diff by retained size, reading the dominator tree, not by allocation count or instance count. Expect one root holding a map with millions of entries, then follow the reference chain to the code that inserts and never removes. Allocation profilers point at churn, which is the wrong signal here.
  4. The candidate that fits this service is an observability label carrying an identifier, such as a request path recorded before templating so that /v1/resources/48213 becomes its own metric series. That grows with distinct ids seen, is independent of rate, and explains the late p99 degradation, since GC cost rises with the size of the live set.

Follow-up

  • Post-GC heap is now flat but resident size still creeps. What are you looking at, and does it matter?
  • How would you have detected this before an OOM, given the nightly restart masked the trend?

Suggested practice checklist

Built from the rounds and topics Bestow candidates report.

Day 1 — Map the Bestow loop

  • Write out the reported sequence: Phone Screen, Technical Interview, Coding Assessment, Technical 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 4 reported rounds, with the weakest marked.

Day 2 — Work Technical interviewing / coding assessments

  • Spend the session on Technical interviewing / coding assessments, which Bestow candidates report being tested on.
  • Write one worked example in Technical interviewing / coding assessments and time yourself on it.

Deliverable: One timed worked example in Technical interviewing / coding assessments.

Day 3 — Work SQL (query writing)

  • Spend the session on SQL (query writing), which Bestow candidates report being tested on.
  • Write one worked example in SQL (query writing) and time yourself on it.

Deliverable: One timed worked example in SQL (query writing).

Day 4 — Work Golang (Go)

  • Spend the session on Golang (Go), which Bestow candidates report being tested on.
  • Write one worked example in Golang (Go) and time yourself on it.

Deliverable: One timed worked example in Golang (Go).

Day 5 — Answer out loud: Technical / Domain Questions

  • Answer aloud, timed: What programming languages are you proficient in, and can you provide examples of projects where you used them?
  • Answer aloud, timed: Describe a challenging technical problem you faced and how you approached solving it.

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

Day 6 — Answer out loud: Problem-Solving / Case Studies

  • Answer aloud, timed: Given a scenario where a life insurance application experiences high latency, how would you investigate and resolve the issue?
  • Answer aloud, timed: Walk us through your thought process in designing a feature for our existing platform.

Deliverable: Spoken answers to 2 reported Problem-Solving / Case Studies question(s), under time.

Day 7 — Answer out loud: Behavioral / Leadership Questions

  • Answer aloud, timed: Describe a situation where you had to collaborate with a difficult team member. How did you handle it?
  • Answer aloud, timed: Can you provide an example of a time when you took initiative on a project?

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

Behavioural preparation

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

What is your experience with cloud technologies, and how have you implemented them in past projects?

Medium · Technical / Domain Questions

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 collaborate with a difficult team member. How did you handle it?

Medium · Behavioral / Leadership Questions

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 a time when you took initiative on a project?

Medium · Behavioral / Leadership Questions

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?

What motivates you to work in the field of software engineering, and how does it align with our mission at Bes

Medium · Behavioral / Leadership Questions

What motivates you to work in the field of software engineering, and how does it align with our mission at Bestow?

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?