A Software Engineer at ServiceTitan is responsible for building and scaling the operating system that powers the multi-billion-dollar field services industry. From HVAC technicians and plumbers to electrical contractors, ServiceTitan's platform acts as the central nervous system for thousands of home and commercial service businesses. As an engineer here, you will design, build, and maintain highly available systems that manage complex scheduling, real-time dispatching, route optimization, mobile payments, and enterprise-grade reporting. The impact of your work is immediate and tangible. Unlike consumer-facing apps where changes might only affect screen time, your code directly influences whether a local business can dispatch a technician to fix a broken heater in freezing temperatures or process payments to pay their employees on time. You will tackle unique engineering challenges at scale, working on deep technical problems that span real-time event processing, complex relational database schemas, and highly responsive mobile and web interfaces. Whether you join a product team focusing on core workflows, a platform team scaling infrastructure, or a specialized group like Contact Center Pro or Ads Product & Platform, you will write code that is robust, performant, and resilient. engineers are expected to balance rapid product delivery with long-term architectural health, ensuring the platform remains stable as the company continues its rapid market expansion. ServiceTitan
Recruiter Screen
reportedInitial conversation with a recruiter to evaluate your fit for the role.
What to demonstrate
- Initial conversation with a recruiter to evaluate your fit for the role
- Depth in Software Engineering (General)
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 Screening
reportedFocus on coding and basic system design to assess technical capabilities.
What to demonstrate
- Focus on coding and basic system design to assess technical capabilities
- Depth in Software Engineering (General)
How to prepare
- Answer aloud and timed: Implement a basic rate limiter for an API endpoint using a sliding window algorithm.
- Answer aloud and timed: Given a list of service technician schedules, merge overlapping time slots to find free windows.
Onsite Loop
reportedComprehensive interviews covering advanced architecture, coding, and behavioral aspects.
What to demonstrate
- Comprehensive interviews covering advanced architecture, coding, and behavioral aspects
- Depth in Software Engineering (General)
How to prepare
- Answer aloud and timed: Design an algorithm to validate a nested set of configuration rules for a dispatch workflow.
- Answer aloud and timed: Design a real-time tracking system for service technicians on their way to a job site.
3 candidate reports. Individual accounts describe a particular role and hiring cycle.
ServiceTitan Software Engineer interview with async/await and system design
My process started with a recruiter screen and then moved into three technical rounds. In the first two, I spent long sessions pair programming. I implemented a custom data structure from an interface, then worked on parallel processing with async/await. The difficulty felt medium or easier, and the interviewers were fair and clear, so I could collaborate and ask questions as I went. The third ro…
Read full experienceServiceTitan Software Engineer interview: difficult technical loops and inattentive evaluation
The process began with recruiter coordination and became a set of deep technical conversations that I found genuinely hard. One version included several coding interviews and a system design discussion. The people were pleasant and my impression of the culture was positive, but I was at the end of a hiring cycle, and that affected the result. In a different technical loop, the difficulty was not…
Read full experienceSoftware Engineer interview at ServiceTitan: slow coding sequence
After a recruiter call, I went through several straightforward coding rounds. They focused on medium LeetCode-style data structures and algorithms. The interviewers were calm and practical, asked clarifying questions, and stayed interested in how I was thinking. I cleared multiple rounds that kept testing much the same skill set, but the whole process took about a month. Several-day pauses appear…
Read full experiencePracHub editorial advice for the preparation topics above.
Think Out Loud
During both coding and system design rounds, your interviewer wants to understand your thought process. Do not code in silence. Explain why you are choosing a specific data structure or why you prefer one database technology over another.
Clarify the Requirements First
Never jump straight into writing code or drawing architecture diagrams. Spend the first few minutes asking clarifying questions to understand the constraints, scale, and exact requirements of the problem.
Focus on the Business Value
When describing your past projects, do not just talk about the technologies you used. Explain why you built it, what business problem it solved, and how it impacted the end-user or the company's bottom line.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Write a function to find the first non-repeating character in a stream of characters.
Write a function to find the first non-repeating character in a stream of characters.
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 an array of integers, return indices of the two numbers such that they add up to a specific target.
Given an array of integers, return indices of the two numbers such that they add up to a specific target.
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 list of service technician schedules, merge overlapping time slots to find free windows.
Given a list of service technician schedules, merge overlapping time slots to find free windows.
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?
Denormalise tenant onto revisions and backfill it live
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
- 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.
- 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.
- 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.
- 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?
Replace offset paging on the resource feed with keyset
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
- 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.
- 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.
- 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.
- 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?
Implement a basic rate limiter for an API endpoint using a sliding window algorithm.
Implement a basic rate limiter for an API endpoint using a sliding window algorithm.
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
Design an algorithm to validate a nested set of configuration rules for a dispatch workflow.
Design an algorithm to validate a nested set of configuration rules for a dispatch workflow.
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?
Design a real-time tracking system for service technicians on their way to a job site.
Design a real-time tracking system for service technicians on their way to a job site.
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?
How would you design a scalable notification system that sends SMS, email, and push notifications to thousands
How would you design a scalable notification system that sends SMS, email, and push notifications to thousands of users simultaneously?
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?
Design a payment processing pipeline that guarantees exactly-once processing for transactions.
Design a payment processing pipeline that guarantees exactly-once processing for transactions.
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?
How would you transition a monolithic service dispatch application into a microservices architecture without d
How would you transition a monolithic service dispatch application into a microservices architecture without downtime?
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?
Design a database schema to support complex, customizable reporting dashboards for enterprise business owners.
Design a database schema to support complex, customizable reporting dashboards for enterprise business owners.
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?
Edge instances grow 400 MB per hour until the nightly restart
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
- 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.
- 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.
- 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.
- 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?
Built from the rounds and topics ServiceTitan candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the ServiceTitan loop
- Write out the reported sequence: Recruiter Screen, Technical Screening, Onsite Loop.
- 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.
02Work Software Engineering (General)
- Spend the session on Software Engineering (General), which ServiceTitan candidates report being tested on.
- Write one worked example in Software Engineering (General) and time yourself on it.
Deliverable: One timed worked example in Software Engineering (General).
03Work Engineering Management
- Spend the session on Engineering Management, which ServiceTitan candidates report being tested on.
- Write one worked example in Engineering Management and time yourself on it.
Deliverable: One timed worked example in Engineering Management.
04Work Backend Development
- Spend the session on Backend Development, which ServiceTitan candidates report being tested on.
- Write one worked example in Backend Development and time yourself on it.
Deliverable: One timed worked example in Backend Development.
05Answer out loud: Coding and Problem Solving
- Answer aloud, timed: Write a function to find the first non-repeating character in a stream of characters.
- Answer aloud, timed: Given an array of integers, return indices of the two numbers such that they add up to a specific target.
Deliverable: Spoken answers to 2 reported Coding and Problem Solving question(s), under time.
06Answer out loud: System Design and Architecture
- Answer aloud, timed: Design a real-time tracking system for service technicians on their way to a job site.
- Answer aloud, timed: How would you design a scalable notification system that sends SMS, email, and push notifications to thousands of users simultaneously?
Deliverable: Spoken answers to 2 reported System Design and Architecture question(s), under time.
07Answer out loud: Behavioral and Core Values
- Answer aloud, timed: Tell me about a time you had to make a technical compromise to meet a tight business deadline.
- Answer aloud, timed: Describe a situation where you disagreed with a product manager's requirement. How did you resolve it?
Deliverable: Spoken answers to 2 reported Behavioral and Core Values question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Tell me about a time you had to make a technical compromise to meet a tight business deadline.
Tell me about a time you had to make a technical compromise to meet a tight business deadline.
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?
Describe a situation where you disagreed with a product manager's requirement. How did you resolve it?
Describe a situation where you disagreed with a product manager's requirement. How did you resolve it?
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?
Talk about a major technical failure you were responsible for. What did you learn, and how did you prevent it
Talk about a major technical failure you were responsible for. What did you learn, and how did you prevent it from happening again?
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?
Give an example of how you mentored a junior engineer or helped level up your engineering team.
Give an example of how you mentored a junior engineer or helped level up your engineering team.
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?
How do you handle a situation where you are assigned a task with highly ambiguous requirements?
How do you handle a situation where you are assigned a task with highly ambiguous requirements?
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?
- 01
Tell me about a time you had to make a technical compromise to meet a tight business deadline.
- 02
Describe a situation where you disagreed with a product manager's requirement. How did you resolve it?
- 03
Talk about a major technical failure you were responsible for. What did you learn, and how did you prevent it from happening again?
- 04
Give an example of how you mentored a junior engineer or helped level up your engineering team.
What is the primary technology stack at ServiceTitan?
ServiceTitan historically has a strong foundation in Microsoft technologies, utilizing C# and.NET for a significant portion of its backend services, SQL Server for data storage, and Azure for cloud infrastructure. The frontend is primarily built using React and TypeScript. However, as the platform scales, various teams also leverage technologies like Go, Python, and modern NoSQL databases where appropriate.
ServiceTitan Software Engineer candidate reports ↗How long does the entire interview process typically take?
The interview process generally takes between 2 to 4 weeks from the initial recruiter screen to the final offer. This timeline can vary depending on candidate availability, the urgency of the hiring team, and the depth of the onsite scheduling loop.
ServiceTitan Software Engineer candidate reports ↗How heavily does ServiceTitan weigh system design versus coding?
Both are highly critical, but the weight shifts based on seniority. For junior to mid-level roles, coding proficiency, clean implementation, and understanding of data structures are heavily emphasized. For senior, staff, and management roles, system design, scalability trade-offs, and architectural vision are the primary differentiators.
ServiceTitan Software Engineer candidate reports ↗Is ServiceTitan open to remote or hybrid work arrangements?
Yes, ServiceTitan offers hybrid and remote-friendly options depending on the specific team, role, and location. Many engineering teams operate in a hybrid model out of offices in California, while others support fully remote engineers across the United States and international hubs.
ServiceTitan Software Engineer candidate reports ↗What topics does ServiceTitan test in interviews?
ServiceTitan interviews most often cover Problem Solving, Stakeholder Management, Stakeholder Communication, Panel Interviewing, and Technical Interviewing. The exact emphasis depends on the specific role you apply for.
ServiceTitan Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01ServiceTitan Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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