The Software Engineer role at Rain is a foundational position focused on building scalable, high-impact financial technology solutions. You will be responsible for designing and implementing systems that directly influence the user experience and the company’s core product offerings. Success in this role requires a blend of deep technical proficiency and the ability to navigate complex, distributed environments. You will work closely with cross-functional teams, including product managers and fellow engineers, to translate business requirements into robust, production-ready code. Because Rain operates in a fast-paced environment, you are expected to take ownership of your deliverables, contribute to architectural decision-making, and uphold high standards for code quality and system performance. This role is not just about writing code; it is about solving critical problems that drive the business forward. ##### Tip Candidates should be prepared for a high-intensity environment. Success at Rain requires balancing rapid feature delivery with the long-term stability and scalability of the system.
Initial Screening
reportedThe first step where candidates are evaluated for basic qualifications and fit.
What to demonstrate
- The first step where candidates are evaluated for basic qualifications and fit
- Depth in System Design
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 Assessments
reportedA series of assessments to evaluate technical capabilities and coding skills.
What to demonstrate
- A series of assessments to evaluate technical capabilities and coding skills
- Depth in System Design
How to prepare
- Answer aloud and timed: Can you walk me through your process for debugging a production-level issue?
- Answer aloud and timed: Describe a situation where you had to refactor legacy code to improve performance.
Final Onsite Assessments
reportedIn-depth evaluations that may include system design and practical coding tasks.
What to demonstrate
- In-depth evaluations that may include system design and practical coding tasks
- Depth in System Design
How to prepare
- Answer aloud and timed: How do you ensure your code is maintainable and scalable?
- Answer aloud and timed: Design a system for [specific product feature] that can handle high throughput.
PracHub editorial advice for the preparation topics above.
Own your narrative
Since interviewers may not have reviewed your resume, have a "pitch" ready that highlights your most impressive technical achievements.
Clarify before coding
Always ask clarifying questions before diving into a coding problem. It shows you think before you act.
Communicate your thought process
Never code in silence. Narrate your reasoning so the interviewer can follow your logic.
Prepare for follow-ups
If you suggest an architecture, be ready for the interviewer to ask, "What if traffic triples?" or "How would you handle a database outage?"
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Explain the technical complexities of your most recent project and its impact.
Explain the technical complexities of your most recent project and its impact.
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?
Describe a situation where you had to refactor legacy code to improve performance.
Describe a situation where you had to refactor legacy code to improve performance.
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?
Track a rolling failure rate per destination for circuit decisions
The egress service delivers about 1,500 webhooks per second across roughly 40,000 destinations, each call bounded by a 10 second timeout. Maintain, per destination, the failure rate over the trailing 60 seconds so a caller can ask before dispatch whether the circuit should open. Attempts arrive as (destination_id, finished_at_ms, outcome). Requirement: amortised O(1) per attempt, with total memory bounded by the destination count rather than by traffic. Give the structure, its exact memory, and the rule that stops a destination with three attempts from opening a circuit.
Approach
- Name the exact-deque version and then reject it as the default. Holding timestamps and advancing a tail pointer past anything older than now minus 60 seconds is a correct two-pointer window at amortised O(1) per attempt, but its memory tracks in-window traffic, so one destination in a retry storm holds hundreds of thousands of entries while thousands of quiet destinations hold none.
- Use a ring of 60 one-second buckets per destination, each bucket a pair of counters for attempts and failures. On an attempt, advance the ring by the elapsed whole seconds, zeroing at most min(elapsed, 60) buckets, then increment the head. That is amortised O(1) with a fixed footprint per destination.
- State the footprint: 60 buckets times two 4-byte counters is 480 bytes of payload per destination, so 40,000 destinations is roughly 20 to 25 MB with per-entry overhead, bounded by the catalogue rather than by the rate. The cost is granularity, since the oldest bucket ages out in whole seconds, which is far tighter than the decision needs.
- Require a minimum sample before the circuit may open. A destination with three attempts and three failures reads as 100 percent and is not evidence; a floor of roughly 20 attempts in the window makes the ratio meaningful, and below that floor use a run of consecutive failures as the trigger instead.
Follow-up
- The fleet is 30 instances and each sees roughly a thirtieth of a destination's traffic. Where does the rate actually live, and what does a per-instance answer get wrong?
- A destination answers in 9.5 seconds and succeeds. It is not failing but it is consuming your per-destination concurrency. What signal should open the circuit here?
How would you structure the database schema for a real-time transaction system?
How would you structure the database schema for a real-time transaction system?
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?
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?
How do you ensure your code is maintainable and scalable?
How do you ensure your code is maintainable and scalable?
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 for [specific product feature] that can handle high throughput.
Design a system for [specific product feature] that can handle high throughput.
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 the trade-offs between choosing a monolithic architecture versus microservices.
Explain the trade-offs between choosing a monolithic architecture versus microservices.
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 approach caching strategies to reduce latency?
How do you approach caching strategies to reduce latency?
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 notification service that scales to millions of users.
Design a notification service that scales to millions of users.
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?
Can you walk me through your process for debugging a production-level issue?
Can you walk me through your process for debugging a production-level issue?
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 Rain candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Rain loop
- Write out the reported sequence: Initial Screening, Technical Assessments, Final Onsite Assessments.
- 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 System Design
- Spend the session on System Design, which Rain 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.
03Work Implementation Skills After Design
- Spend the session on Implementation Skills After Design, which Rain candidates report being tested on.
- Write one worked example in Implementation Skills After Design and time yourself on it.
Deliverable: One timed worked example in Implementation Skills After Design.
04Work Coding Interviews
- Spend the session on Coding Interviews, which Rain candidates report being tested on.
- Write one worked example in Coding Interviews and time yourself on it.
Deliverable: One timed worked example in Coding Interviews.
05Answer out loud: Technical Proficiency and Coding
- Answer aloud, timed: Explain the technical complexities of your most recent project and its impact.
- Answer aloud, timed: How do you handle concurrency in your current tech stack?
Deliverable: Spoken answers to 2 reported Technical Proficiency and Coding question(s), under time.
06Answer out loud: System Design and Architecture
- Answer aloud, timed: Design a system for [specific product feature] that can handle high throughput.
- Answer aloud, timed: How would you structure the database schema for a real-time transaction system?
Deliverable: Spoken answers to 2 reported System Design and Architecture question(s), under time.
07Answer out loud: Behavioral and Cultural Alignment
- Answer aloud, timed: Tell me about a time you disagreed with a technical decision; how did you resolve it?
- Answer aloud, timed: Describe a challenging project where you had to mentor a junior peer.
Deliverable: Spoken answers to 2 reported Behavioral and Cultural Alignment 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 concurrency in your current tech stack?
How do you handle concurrency in your current tech stack?
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 disagreed with a technical decision; how did you resolve it?
Tell me about a time you disagreed with a technical decision; 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?
Describe a challenging project where you had to mentor a junior peer.
Describe a challenging project where you had to mentor a junior peer.
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 feedback, especially when it is critical?
How do you handle feedback, especially when it is critical?
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 a time you had to work under a tight deadline.
Give an example of a time you had to work under a tight 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?
How do you contribute to a collaborative and inclusive engineering culture?
How do you contribute to a collaborative and inclusive engineering culture?
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 concurrency in your current tech stack?
- 02
Tell me about a time you disagreed with a technical decision; how did you resolve it?
- 03
Describe a challenging project where you had to mentor a junior peer.
- 04
How do you handle feedback, especially when it is critical?
How difficult are the technical interviews compared to other tech companies?
The technical rounds at Rain are considered quite challenging, particularly the system design and implementation sessions. Expect a high bar for both technical precision and architectural foresight.
Rain Software Engineer candidate reports ↗What should I do if my interviewer is not prepared?
If an interviewer appears unfamiliar with your background, take the initiative to provide a structured, 2-minute overview of your experience and your most relevant projects. This demonstrates leadership and keeps the interview focused on your strengths.
Rain Software Engineer candidate reports ↗Is the process always remote?
Rain often conducts remote interviews, but you should confirm the format with your recruiter. Ensure your setup is professional and that you have a quiet environment to avoid technical distractions.
Rain Software Engineer candidate reports ↗How long does the entire process take?
The process can vary, but generally, it moves from the initial screen to the final onsite over several weeks. Stay proactive with follow-ups if you haven't received feedback within the expected window.
Rain Software Engineer candidate reports ↗What topics does Rain test in interviews?
Rain interviews most often cover System Design, Recruiter Communication & Responsiveness, Implementation Skills After Design, Sales Process Management (Interview Stages), and Coding Interviews. The exact emphasis depends on the specific role you apply for.
Rain 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.
- 01Rain 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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