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GEN Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at GEN, you are at the heart of building solutions that protect, empower, and simplify the digital lives of millions of users globally. You will work on sophisticated platforms that require a blend of high-performance backend engineering, data integrity, and a deep focus on security and reliability. Whether you are optimizing core infrastructure or developing new features for flagship consumer products, your work directly influences the safety and digital experience of our user base. This role demands more than just technical proficiency; it requires a mindset geared toward scalability, clean code, and user-centric design. You will operate within cross-functional teams, collaborating closely with product managers, QA engineers, and security specialists to solve complex technical challenges.

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

Focus areas

  • Data Structures & Algorithms (DSA)
  • SQL
  • Algorithms (coding problems)

The GEN interview process

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

Initial Screening

The process begins with an initial screening by a recruiter to assess your fit for the role.

What to demonstrate

  • The process begins with an initial screening by a recruiter to assess your fit for the role
  • Depth in Data Structures & Algorithms (DSA)

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 Evaluations

Candidates undergo in-depth technical assessments to evaluate their theoretical knowledge and practical skills.

What to demonstrate

  • Candidates undergo in-depth technical assessments to evaluate their theoretical knowledge and practical skills
  • Depth in Data Structures & Algorithms (DSA)

How to prepare

  • Answer aloud and timed: Can you explain the practical application of SOLID principles in your recent projects?
  • Answer aloud and timed: What is your experience with regex and string manipulation in Python?

Multiple Technical Rounds

For some roles, candidates may face multiple technical rounds with different team members to assess versatility.

What to demonstrate

  • For some roles, candidates may face multiple technical rounds with different team members to assess versatility
  • Depth in Data Structures & Algorithms (DSA)

How to prepare

  • Answer aloud and timed: How do you approach debugging a complex issue in a live production app?
  • Answer aloud and timed: Solve a given problem using data structures and algorithms (typically ranging from easy to medium complexity).

Where candidates lose points

Prioritize Communication

When solving problems, think out loud. Interviewers at GEN are interested in your thought process as much as the final code.

Master the Basics

Do not overlook "easy" or "basic" concepts. Many interviews focus on core fundamentals rather than obscure, complex algorithms.

Prepare Questions for Them

Always have thoughtful questions ready about the team's culture, their current technical challenges, and how they define success for the role.

Review Your Resume

Be prepared to dive deep into every project you have listed. If you mention a tool or technology, be ready to discuss it in depth.

Questions & practice

Solve a given problem using data structures and algorithms (typically ranging from easy to medium complexity).

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 specific coding task, implement a solution that balances performance with readability.

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?

Explain your thought process while live-coding a solution during a screen-share session.

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?

Write a SQL query to extract or manipulate data from a relational database.

Medium · Coding & Algorithms

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?

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?

Explain the difference between black box and white box testing.

Medium · Technical & Domain Knowledge

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 do you ensure clean code and maintainable architecture in a production environment?

Medium · Technical & Domain Knowledge

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?

Can you explain the practical application of SOLID principles in your recent projects?

Medium · Technical & Domain Knowledge

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 do you approach debugging a complex issue in a live production app?

Medium · Technical & Domain Knowledge

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 GEN candidates report.

Day 1 — Map the GEN loop

  • Write out the reported sequence: Initial Screening, Technical Evaluations, Multiple Technical 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 Data Structures & Algorithms (DSA)

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

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

Day 3 — Work SQL

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

Deliverable: One timed worked example in SQL.

Day 4 — Work Algorithms (coding problems)

  • Spend the session on Algorithms (coding problems), which GEN candidates report being tested on.
  • Write one worked example in Algorithms (coding problems) and time yourself on it.

Deliverable: One timed worked example in Algorithms (coding problems).

Day 5 — Answer out loud: Technical & Domain Knowledge

  • Answer aloud, timed: Explain the difference between black box and white box testing.
  • Answer aloud, timed: How do you ensure clean code and maintainable architecture in a production environment?

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

Day 6 — Answer out loud: Coding & Algorithms

  • Answer aloud, timed: Solve a given problem using data structures and algorithms (typically ranging from easy to medium complexity).
  • Answer aloud, timed: Write a SQL query to extract or manipulate data from a relational database.

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

Day 7 — Answer out loud: Behavioral & Experience

  • Answer aloud, timed: Walk me through a challenging project from your past experience and your specific contribution to it.
  • Answer aloud, timed: Describe a time you had to resolve a technical disagreement with a team member.

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

Behavioural preparation

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

What is your experience with regex and string manipulation in Python?

Medium · Technical & Domain Knowledge

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?

Walk me through a challenging project from your past experience and your specific contribution to it.

Medium · Behavioral & Experience

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 time you had to resolve a technical disagreement with a team member.

Medium · Behavioral & Experience

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 your tasks when working on multiple high-priority deliverables?

Medium · Behavioral & Experience

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?

Tell me about a time you identified a critical bug or performance bottleneck—how did you address it?

Medium · Behavioral & Experience

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?