Interview guides · First American Financial

First American Financial Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at First American Financial, you play a vital role in building and maintaining the digital infrastructure that powers one of the nation's largest providers of title insurance, settlement services, and risk solutions for real estate transactions. Your work directly impacts the efficiency and security of financial transactions for millions of customers, requiring a balance of technical rigor and a keen understanding of real-time, high-stakes data environments. You will be part of a team tasked with solving complex problems that range from optimizing database architectures to developing robust, scalable applications. Whether you are working on internal tools or customer-facing platforms, the role demands a high level of accountability.

This guide is scoped to a Software Engineer candidate at First American Financial.

Focus areas

Data Structures & Algorithms (DSA)
System Design
Coding Interview Problem Solving

The First American Financial interview process

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

Initial Contact

The process begins with initial contact to discuss the opportunity and gauge interest.

What to demonstrate

The process begins with initial contact to discuss the opportunity and gauge interest
Depth in Data Structures & Algorithms (DSA)

How to prepare

Answer aloud and timed: Explain the difference between interface and abstract classes in Object-Oriented Programming (OOP).
Answer aloud and timed: Describe the core principles of SOLID design and how you apply them in your code.

Technical Assessments

Candidates undergo technical assessments to evaluate their skills and knowledge.

What to demonstrate

Candidates undergo technical assessments to evaluate their skills and knowledge
Depth in Data Structures & Algorithms (DSA)

How to prepare

Answer aloud and timed: Can you explain how SQL joins function and when you would use a left join versus an inner join?
Answer aloud and timed: Explain the difference between a temp table and a table variable in SQL Server.

Behavioral Deep Dives

In-depth behavioral interviews to assess cultural fit and teamwork capabilities.

What to demonstrate

In-depth behavioral interviews to assess cultural fit and teamwork capabilities
Depth in Data Structures & Algorithms (DSA)

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 deep dives above and write down what you would ask to confirm before it.

Final Managerial Rounds

Final interviews with management to discuss leadership qualities and overall fit.

What to demonstrate

Final interviews with management to discuss leadership qualities and overall fit
Depth in Data Structures & Algorithms (DSA)

How to prepare

Answer aloud and timed: How would you handle a situation where you need to optimize a slow-performing database query?
Answer aloud and timed: Describe a time you had to debug a difficult issue in a production environment.

Where candidates lose points

Own your resume

Every line on your resume is fair game. If you list a technology, be prepared to answer deep-dive questions about it.

Practice your "Why

Have a clear, compelling answer for why you want to work at First American Financial. Connect your personal career goals with the company's mission.

Prepare for ambiguity

Some interviewers may ask open-ended questions to see how you structure your approach. Don't panic; take a moment to organize your thoughts before speaking.

Be professional

Even if you feel the interview is informal, maintain a professional tone and appearance. It reflects your respect for the team's time and the role.

Questions & practice

Walk me through your approach to solving a complex coding challenge.

Medium · Problem-Solving and Algorithms

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
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 set of requirements, how do you determine the best data structure for the job?

Medium · Problem-Solving and Algorithms

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
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 strategy for writing unit tests for a new feature.

Medium · Problem-Solving and Algorithms

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
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?

Can you explain how SQL joins function and when you would use a left join versus an inner join?

Medium · Technical Fundamentals and Domain Knowle

Approach

Name the grain you start from and join outward from it.
Check whether any join is one-to-many before aggregating, or the sums inflate.
Say which index the query would use, and what makes it unusable.
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 the difference between a temp table and a table variable in SQL Server.

Medium · Technical Fundamentals and Domain Knowle

Approach

Name the grain you start from and join outward from it.
Check whether any join is one-to-many before aggregating, or the sums inflate.
Say which index the query would use, and what makes it unusable.
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?

What is parameter sniffing in the context of SQL performance?

Medium · Technical Fundamentals and Domain Knowle

Approach

Name the grain you start from and join outward from it.
Check whether any join is one-to-many before aggregating, or the sums inflate.
Say which index the query would use, and what makes it unusable.
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?

How would you handle a situation where you need to optimize a slow-performing database query?

Medium · Problem-Solving and Algorithms

Approach

Name the grain you start from and join outward from it.
Check whether any join is one-to-many before aggregating, or the sums inflate.
Say which index the query would use, and what makes it unusable.
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 the difference between interface and abstract classes in Object-Oriented Programming (OOP).

Medium · Technical Fundamentals and Domain Knowle

Approach

Clarify what is being asked and what a complete answer contains.
State your assumptions explicitly before working the problem.
Say what you would check first and why it is the highest-information step.
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 core principles of SOLID design and how you apply them in your code.

Medium · Technical Fundamentals and Domain Knowle

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
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?

Listing latency scales with page size, not with filters

Easy · n+1 · latency · query batching

The tenant listing endpoint reads resource filtered by tenant_id and status, ordered by updated_at DESC, and returns each row plus the owner's display name from app_user and the actor of that resource's latest resource_revision. p99 is 55 ms at 10 rows per page and 1.4 s at 200. Database telemetry shows 401 statements per request, each under 1 ms, and nothing in the slow-query log. Diagnose the cause and give the fix, stating the statement count per request and the p99 you expect afterwards.

Approach

Read the counters before forming a theory. 401 statements for 200 rows is one driver query plus two per row, and sub-millisecond execution with an empty slow-query log rules out a bad plan. The time is round trips, which is why it is invisible in every per-query metric and scales with rows returned rather than with filter selectivity.
Name the two per-row statements from their normalised text: a single-row app_user lookup by user_id, and a resource_revision lookup by resource_id ordered by version DESC LIMIT 1. Confirm by dropping those two response fields and watching the statement count fall to one. That locates the calls in the serialisation layer, not the repository.
Check that the arithmetic accounts for the whole gap. Measure one round trip to the replica in isolation; 400 trips at roughly 3 ms of network plus 0.2 ms of execution is about 1.3 s on top of a 55 ms baseline, which matches. If the multiplication had fallen short, the N+1 would only be part of the story and you would keep looking.
Batch both lookups. Collect owner_user_ids and resource_ids from the driver query, then issue WHERE tenant_id = $1 AND user_id = ANY($2) for the users, and PostgreSQL's SELECT DISTINCT ON (resource_id) ... WHERE resource_id = ANY($2) ORDER BY resource_id, version DESC for the latest revision, which the UNIQUE (resource_id, version) index serves directly. On an engine without DISTINCT ON, use a lateral join or a row_number window. Three statements per request at any page size.

Follow-up

The page size is capped at 200 today. What breaks first if it is raised to 2,000, and is it still this bug?
How do you stop the next N+1 from reaching production, given that no individual query is slow and the endpoint's tests pass?

Suggested practice checklist

Built from the rounds and topics First American Financial candidates report.

Day 1 — Map the First American Financial loop

Write out the reported sequence: Initial Contact, Technical Assessments, Behavioral Deep Dives, Final Managerial 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 4 reported rounds, with the weakest marked.

Day 2 — Work Data Structures & Algorithms (DSA)

Spend the session on Data Structures & Algorithms (DSA), which First American Financial 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 System Design

Spend the session on System Design, which First American Financial 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 4 — Work Coding Interview Problem Solving

Spend the session on Coding Interview Problem Solving, which First American Financial candidates report being tested on.
Write one worked example in Coding Interview Problem Solving and time yourself on it.

Deliverable: One timed worked example in Coding Interview Problem Solving.

Day 5 — Answer out loud: Technical Fundamentals and Domain Knowledge

Answer aloud, timed: Explain the difference between interface and abstract classes in Object-Oriented Programming (OOP).
Answer aloud, timed: Describe the core principles of SOLID design and how you apply them in your code.

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

Day 6 — Answer out loud: Problem-Solving and Algorithms

Answer aloud, timed: Walk me through your approach to solving a complex coding challenge.
Answer aloud, timed: How would you handle a situation where you need to optimize a slow-performing database query?

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

Day 7 — Answer out loud: Behavioral and Leadership

Answer aloud, timed: Tell me about a time you had a conflict with a teammate and how you resolved it.
Answer aloud, timed: Why are you interested in joining First American Financial, and what do you know about our values?

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

Behavioural preparation

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

Describe a time you had to debug a difficult issue in a production environment.

Medium · Problem-Solving and Algorithms

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
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?