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Shift Technology Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer at Shift Technology plays a pivotal role in shaping the future of insurance decision automation. The company leverages advanced artificial intelligence and machine learning to help global insurance providers detect fraud, automate claims processing, and optimize underwriting decisions. In this role, you are not just writing code; you are building the secure, high-throughput, and resilient infrastructure required to ingest, process, and analyze massive volumes of complex financial and personal data. The impact of your work is immediate and highly visible. By developing clean, optimized, and scalable backend services and intuitive frontend interfaces, you directly enable insurance companies to detect sophisticated fraud networks in real time.

This guide is scoped to a Software Engineer candidate at Shift Technology.

Focus areas

  • Algorithmic problem solving
  • Time and space complexity (Big O)
  • Design patterns

The Shift Technology interview process

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

HR Screening

Initial screening to evaluate candidate's background and fit for the role.

What to demonstrate

  • Initial screening to evaluate candidate's background and fit for the role
  • Depth in Algorithmic problem solving

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

Phone screen with an engineer to assess technical skills.

What to demonstrate

  • Phone screen with an engineer to assess technical skills
  • Depth in Algorithmic problem solving

How to prepare

  • Answer aloud and timed: Write an algorithm to detect duplicate records within a large dataset of insurance claims.
  • Answer aloud and timed: Solve a classic array-manipulation problem on a whiteboard and discuss edge cases.

Intensive Technical Rounds

Multiple rounds focusing on live coding, system design, and clean code principles.

What to demonstrate

  • Multiple rounds focusing on live coding, system design, and clean code principles
  • Depth in Algorithmic problem solving

How to prepare

  • Answer aloud and timed: What is the difference between an interface and an abstract class, and when would you use each?
  • Answer aloud and timed: Explain the SOLID design principles and how you apply them in your daily development.

Interviews with Leadership

Final interviews with engineering managers, directors, or executive leadership to evaluate overall fit.

What to demonstrate

  • Final interviews with engineering managers, directors, or executive leadership to evaluate overall fit
  • Depth in Algorithmic problem solving

How to prepare

  • Answer aloud and timed: Walk through a design pattern (such as Factory or Singleton) and explain its real-world utility.
  • Answer aloud and timed: How do you ensure your code remains highly testable and maintainable over time?

Where candidates lose points

Verify the Interview Language

Even if you are interviewing in a non-English speaking country (such as France or Spain), be prepared for technical rounds to be conducted in English to assess your ability to collaborate globally.

Clarify Requirements Early

During live coding exercises, do not jump straight into writing code. Spend the first few minutes asking clarifying questions, defining inputs/outputs, and discussing your proposed approach with your interviewer.

Brush Up on SQL Basics

Candidates are frequently evaluated on their database knowledge. Ensure you can confidently explain indexing, joins, and transaction isolation levels.

Show Resilience in Redundant Rounds

You may encounter some repetitive technical questions or coding exercises across different interview stages. Maintain your enthusiasm and deliver consistent, high-quality answers in every round.

Questions & practice

Explain the time and space complexity (Big O notation) of your proposed solution.

Medium · Algorithms & Data Structures

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 search algorithm to run in logarithmic time instead of linear time?

Medium · Algorithms & Data Structures

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 an algorithm to detect duplicate records within a large dataset of insurance claims.

Medium · Algorithms & Data Structures

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?

Solve a classic array-manipulation problem on a whiteboard and discuss edge cases.

Medium · Algorithms & Data Structures

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 does database indexing work under the hood, and how does it impact read versus write performance?

Medium · Databases & System Performance

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?

Explain the difference between synchronous and asynchronous I/O operations, particularly regarding file and da

Medium · Databases & System Performance

Explain the difference between synchronous and asynchronous I/O operations, particularly regarding file and database access.

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 a slow-running SQL query that joins multiple large transaction tables?

Medium · Databases & System Performance

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?

Explain why the owner filter ignores the listing index

Medium · composite index · query plans · sort elimination

The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.

Approach

  1. Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
  2. For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
  3. Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
  4. Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.

Follow-up

  • 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
  • A dashboard runs this for 40 owners in one page load. What changes about the design?

What is the difference between an interface and an abstract class, and when would you use each?

Medium · Object-Oriented Programming & Design Pat

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 the SOLID design principles and how you apply them in your daily development.

Medium · Object-Oriented Programming & Design Pat

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 through a design pattern (such as Factory or Singleton) and explain its real-world utility.

Medium · Object-Oriented Programming & Design Pat

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 your code remains highly testable and maintainable over time?

Medium · Object-Oriented Programming & Design Pat

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 strategies do you use to prevent deadlocks in highly concurrent database environments?

Medium · Databases & System Performance

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 Shift Technology candidates report.

Day 1 — Map the Shift Technology loop

  • Write out the reported sequence: HR Screening, Technical Assessment, Intensive Technical Rounds, Interviews with Leadership.
  • 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 Algorithmic problem solving

  • Spend the session on Algorithmic problem solving, which Shift Technology candidates report being tested on.
  • Write one worked example in Algorithmic problem solving and time yourself on it.

Deliverable: One timed worked example in Algorithmic problem solving.

Day 3 — Work Time and space complexity (Big O)

  • Spend the session on Time and space complexity (Big O), which Shift Technology candidates report being tested on.
  • Write one worked example in Time and space complexity (Big O) and time yourself on it.

Deliverable: One timed worked example in Time and space complexity (Big O).

Day 4 — Work Design patterns

  • Spend the session on Design patterns, which Shift Technology candidates report being tested on.
  • Write one worked example in Design patterns and time yourself on it.

Deliverable: One timed worked example in Design patterns.

Day 5 — Answer out loud: Algorithms & Data Structures

  • Answer aloud, timed: Explain the time and space complexity (Big O notation) of your proposed solution.
  • Answer aloud, timed: How would you optimize a search algorithm to run in logarithmic time instead of linear time?

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

Day 6 — Answer out loud: Object-Oriented Programming & Design Patterns

  • Answer aloud, timed: What is the difference between an interface and an abstract class, and when would you use each?
  • Answer aloud, timed: Explain the SOLID design principles and how you apply them in your daily development.

Deliverable: Spoken answers to 2 reported Object-Oriented Programming & Design Patterns question(s), under time.

Day 7 — Answer out loud: Databases & System Performance

  • Answer aloud, timed: How does database indexing work under the hood, and how does it impact read versus write performance?
  • Answer aloud, timed: Explain the difference between synchronous and asynchronous I/O operations, particularly regarding file and database access.

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

Behavioural preparation

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

Walk me through your professional resume and highlight a project where you solved a complex technical challeng

Medium · Behavioral & Experience

Walk me through your professional resume and highlight a project where you solved a complex technical challenge.

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 situations where you disagree with a technical decision made by your team lead?

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 when you had to work with a legacy codebase. How did you approach refactoring 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?

Why are you interested in joining Shift Technology, and how do you see your skills contributing to our fraud-d

Medium · Behavioral & Experience

Why are you interested in joining Shift Technology, and how do you see your skills contributing to our fraud-detection products?

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?