As a Software Engineer at Regal, you will build and scale the industry-leading AI Agent Platform that is redefining how businesses orchestrate customer communications. Founded in 2020 and backed by $82M from top-tier investors like Emergence Capital and Homebrew, Regal empowers high-growth brands to deploy sophisticated, data-connected AI agents. These agents handle millions of high-stakes interactions across VoIP, SMS, and email, driving over $7B in customer revenue and processing more than 250MM+ calls. In this role, you are not just writing code; you are owning complex, end-to-end systems that directly impact the company's rapid growth and bottom line. You will work on a cutting-edge tech stack that includes React, NestJS, GraphQL, TypeScript, Python, Postgres,,, and. The engineering team is tasked with solving hard problems around real-time event streaming, high-throughput APIs, and seamless AI/ML pipeline integrations. Redis Kinesis DynamoDB ##### Tip Regal champions an in-person culture at its Midtown Manhattan headquarters, requiring a hybrid schedule of Tuesday, Wednesday, and Thursday in-office. This setup fosters rapid collaboration, mentorship, and high-velocity engineering output. Ultimately, a Software Engineer at Regal is a product-minded builder. You will collaborate closely with product and design teams to ship features that immediately reach a massive, active user base.
Behavioral and Situational Screen
reportedInitial conversation with the hiring manager focusing on past experiences and system design approach.
What to demonstrate
- Initial conversation with the hiring manager focusing on past experiences and system design approach
- Depth in Real-time event streaming architecture
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 and situational screen above and write down what you would ask to confirm before it.
Technical Rounds
reportedMedium-to-difficult algorithmic coding challenges in a shadow interviewer format on a virtual whiteboard.
What to demonstrate
- Medium-to-difficult algorithmic coding challenges in a shadow interviewer format on a virtual whiteboard
- Depth in Real-time event streaming architecture
How to prepare
- Answer aloud and timed: Design an efficient algorithm to find all unique triplets in an array that sum up to zero.
- Answer aloud and timed: Solve a classic string manipulation or graph traversal problem, ensuring you can explain the exact time complexity of your solution.
Practical Live Coding
reportedHands-on coding and system integration exercises alongside a behavioral wrap-up.
What to demonstrate
- Hands-on coding and system integration exercises alongside a behavioral wrap-up
- Depth in Real-time event streaming architecture
How to prepare
- Answer aloud and timed: Optimize a nested-loop solution to run in linear time using a hash map or two-pointer approach.
- Answer aloud and timed: How would you design a real-time notification system that handles millions of SMS and VoIP events daily without dropping messages?
PracHub editorial advice for the preparation topics above.
Think Out Loud
During algorithmic coding rounds, never code in silence. Talk your interviewer through your logic, explain the trade-offs of your chosen data structures, and state your complexity analysis clearly.
Be Ready to Pivot
If an interviewer questions your time complexity or asks if you can optimize further, do not get defensive. Take a second to re-evaluate, walk through your logic, and pivot to an alternative solution if necessary.
Focus on Real-World Scale
When discussing system design, always frame your answers around high throughput, low latency, and fault tolerance. Mention real-world tools like Kinesis, Redis, and DynamoDB to show you understand modern cloud architectures.
If your practical live coding interviewer seems quiet or disengaged, do not let it throw you off your game
Focus on delivering clean, modular, and well-tested code, and proactively explain your progress to keep the session interactive.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Given an array of integers, find the contiguous subarray which has the largest sum and return its sum.
Given an array of integers, find the contiguous subarray which has the largest sum and return its sum.
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?
Implement a function to find the longest common prefix string amongst an array of strings.
Implement a function to find the longest common prefix string amongst an array of strings.
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?
Solve a classic string manipulation or graph traversal problem, ensuring you can explain the exact time comple
Solve a classic string manipulation or graph traversal problem, ensuring you can explain the exact time complexity of your solution.
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?
Optimize a nested-loop solution to run in linear time using a hash map or two-pointer approach.
Optimize a nested-loop solution to run in linear time using a hash map or two-pointer approach.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- 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?
Hold a per-tenant active cap against concurrent creates
A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.
Approach
- Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
- Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
- Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
- State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.
Follow-up
- A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
- The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?
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?
Design an efficient algorithm to find all unique triplets in an array that sum up to zero.
Design an efficient algorithm to find all unique triplets in an array that sum up to zero.
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 real-time notification system that handles millions of SMS and VoIP events daily withou
How would you design a real-time notification system that handles millions of SMS and VoIP events daily without dropping messages?
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?
Explain how you would structure an API gateway using NestJS and GraphQL to ensure high observability and low l
Explain how you would structure an API gateway using NestJS and GraphQL to ensure high observability and low latency.
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?
Describe your approach to database selection: when would you choose Postgres versus a NoSQL solution like Dyna
Describe your approach to database selection: when would you choose Postgres versus a NoSQL solution like DynamoDB?
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 system that integrates third-party LLM APIs to dynamically generate and send personalized customer re
Design a system that integrates third-party LLM APIs to dynamically generate and send personalized customer responses.
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 do you use LLMs or AI-assisted tools to act as a force multiplier in your daily coding, debugging, and doc
How do you use LLMs or AI-assisted tools to act as a force multiplier in your daily coding, debugging, and documentation workflows?
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- 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?
Tell me about a time you had to debug a critical production outage under pressure. How did you identify the ro
Tell me about a time you had to debug a critical production outage under pressure. How did you identify the root cause and prevent it from happening again?
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- 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?
Built from the rounds and topics Regal candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Regal loop
- Write out the reported sequence: Behavioral and Situational Screen, Technical Rounds, Practical Live Coding.
- 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 Real-time event streaming architecture
- Spend the session on Real-time event streaming architecture, which Regal candidates report being tested on.
- Write one worked example in Real-time event streaming architecture and time yourself on it.
Deliverable: One timed worked example in Real-time event streaming architecture.
03Work LLMs (Large Language Models)
- Spend the session on LLMs (Large Language Models), which Regal candidates report being tested on.
- Write one worked example in LLMs (Large Language Models) and time yourself on it.
Deliverable: One timed worked example in LLMs (Large Language Models).
04Work Node.js
- Spend the session on Node.js, which Regal candidates report being tested on.
- Write one worked example in Node.js and time yourself on it.
Deliverable: One timed worked example in Node.js.
05Answer out loud: Coding & Algorithmic Problem-Solving
- Answer aloud, timed: Given an array of integers, find the contiguous subarray which has the largest sum and return its sum.
- Answer aloud, timed: Implement a function to find the longest common prefix string amongst an array of strings.
Deliverable: Spoken answers to 2 reported Coding & Algorithmic Problem-Solving question(s), under time.
06Answer out loud: System Design & Architecture
- Answer aloud, timed: How would you design a real-time notification system that handles millions of SMS and VoIP events daily without dropping messages?
- Answer aloud, timed: Explain how you would structure an API gateway using NestJS and GraphQL to ensure high observability and low latency.
Deliverable: Spoken answers to 2 reported System Design & Architecture question(s), under time.
07Answer out loud: Behavioral & Situational Leadership
- Answer aloud, timed: Tell me about a time you had to take ownership of a project end-to-end. What challenges did you face, and how did you align stakeholders?
- Answer aloud, timed: Describe a situation where you had a disagreement with a manager or peer regarding a technical design choice. How did you resolve it?
Deliverable: Spoken answers to 2 reported Behavioral & Situational Leadership 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.
How do you handle rate-limiting and backpressure in a high-concurrency event-streaming architecture?
How do you handle rate-limiting and backpressure in a high-concurrency event-streaming architecture?
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?
Tell me about a time you had to take ownership of a project end-to-end. What challenges did you face, and how
Tell me about a time you had to take ownership of a project end-to-end. What challenges did you face, and how did you align stakeholders?
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 had a disagreement with a manager or peer regarding a technical design choice.
Describe a situation where you had a disagreement with a manager or peer regarding a technical design choice. 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?
How do you approach mentoring junior engineers and raising the overall engineering standards of your team?
How do you approach mentoring junior engineers and raising the overall engineering standards of your 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?
- 01
How do you handle rate-limiting and backpressure in a high-concurrency event-streaming architecture?
- 02
Tell me about a time you had to take ownership of a project end-to-end. What challenges did you face, and how did you align stakeholders?
- 03
Describe a situation where you had a disagreement with a manager or peer regarding a technical design choice. How did you resolve it?
- 04
How do you approach mentoring junior engineers and raising the overall engineering standards of your team?
What is the difficulty level of the coding interviews at Regal?
The coding rounds are average to difficult, typically featuring medium-level algorithmic questions similar to those found on popular competitive coding platforms. The key is not just solving the problem, but explaining your time and space complexity with extreme precision.
Regal Software Engineer candidate reports ↗What is the hybrid work policy for engineers?
Regal has built a highly collaborative, in-office culture. Engineers are required to work from the Midtown Manhattan headquarters in New York City on Tuesdays, Wednesdays, and Thursdays, with the option to work remotely on Mondays and Fridays.
Regal Software Engineer candidate reports ↗How does Regal view the use of AI tools during the interview or on the job?
Regal highly values AI-assisted development. They actively look for candidates who are fluent in using LLMs to accelerate their workflows, write tests, and document code, provided they maintain rigorous engineering and security standards.
Regal Software Engineer candidate reports ↗What is the engineering culture like at Regal?
The culture is fast-paced, highly entrepreneurial, and values-driven. Engineers are given immense ownership of their projects, and there is a strong emphasis on continuous learning, mutual mentorship, and high-velocity shipping.
Regal Software Engineer candidate reports ↗What topics does Regal test in interviews?
Regal interviews most often cover SQL Proficiency, Real-time event streaming architecture, Customer handling (difficult customers), Checkout & Payments Product Domain, and LLMs (Large Language Models). The exact emphasis depends on the specific role you apply for.
Regal 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.
- 01Regal 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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