At Relace, a Software Engineer is not just a coder, but a product builder and problem solver who directly shapes the future of our platform. Whether you are optimizing infrastructure, crafting seamless frontend interfaces, driving user acquisition through growth engineering, or advocating for our developer community, your work has a direct impact on our users. Relace relies on its engineering team to build highly reliable, performant, and intuitive tools that solve complex modern workflows. The engineering culture at Relace is rooted in high autonomy, rapid iteration, and deep technical curiosity. Because our engineering team is lean and highly collaborative, every Software Engineer is expected to take complete ownership of their domain. You will work closely with cross-functional partners in product, design, and marketing to translate ambitious ideas into production-ready software. This role is highly critical because Relace operates in a space where performance, scalability, and user experience are major differentiators. From building robust APIs to scaling real-time distributed systems, the technical challenges you will tackle here require both creative problem-solving and disciplined engineering practices.
Recruiter Screen
reportedInitial conversational screen with a recruiter to discuss your background, career goals, and alignment with the company's mission.
What to demonstrate
- Initial conversational screen with a recruiter to discuss your background, career goals, and alignment with the company's mission
- Depth in Infrastructure Engineering
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 Screen
reportedHands-on coding or system design discussion to evaluate technical capabilities.
What to demonstrate
- Hands-on coding or system design discussion to evaluate technical capabilities
- Depth in Infrastructure Engineering
How to prepare
- Answer aloud and timed: Design and implement an in-memory key-value store that supports basic operations along with time-based data expiration (TTL).
- Answer aloud and timed: Write a function to merge overlapping intervals and explain how you would optimize it for extremely large datasets.
Onsite Loop
reportedComprehensive interview involving architecture, coding, collaboration, and behavioral scenarios with various team members.
What to demonstrate
- Comprehensive interview involving architecture, coding, collaboration, and behavioral scenarios with various team members
- Depth in Infrastructure Engineering
How to prepare
- Answer aloud and timed: Design a real-time collaborative document editing system, focusing on conflict resolution strategies and data synchronization.
- Answer aloud and timed: How would you architect a highly scalable telemetry and logging pipeline to ingest millions of events per second with minimal latency?
PracHub editorial advice for the preparation topics above.
Communicate your thought process
Throughout your technical interviews, talk through your reasoning out loud. Interviewers are more interested in how you approach, decompose, and solve a problem than they are in you getting the perfect syntax on your first attempt.
Ask clarifying questions
Our interview questions can sometimes be intentionally open-ended. Before diving into a solution, clarify the requirements, constraints, and assumptions with your interviewer.
Show your passion for the product
We love working with engineers who are genuinely excited about our mission and the space we operate in. Take some time to explore our product and developer ecosystem before your interviews.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Given a list of dependency pairs, write a function to determine a valid build order, and identify if a circula
Given a list of dependency pairs, write a function to determine a valid build order, and identify if a circular dependency exists.
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?
Write a function to merge overlapping intervals and explain how you would optimize it for extremely large data
Write a function to merge overlapping intervals and explain how you would optimize it for extremely large datasets.
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?
Merge partitioned event streams into one ordered feed with bounded lateness
The read-model service consumes 64 log partitions carrying about 4,000 events per second in total. Each partition is ordered within itself, but partitions drift by up to 30 seconds, and the activity feed must present a tenant's events in occurred_at order. Produce the merge. State its complexity, the buffer it requires in events and in bytes, what happens when one partition is idle, and what you do with an event that arrives after you have already emitted its position. Payloads average 1 KB.
Approach
- Merge with a min-heap over the 64 partition heads keyed on (occurred_at, event_id): O(log P) per event and O(n log P) overall. The tie-break on event_id is what makes the output deterministic when two partitions carry the same millisecond, which matters because the feed is paginated and a non-deterministic order reorders pages under the reader.
- Emitting the heap head is only correct once every partition has produced everything up to that timestamp, so the emit condition is a watermark: the minimum across partitions of the highest occurred_at seen, less the allowed lateness. Events are held until the watermark passes them, which is what turns individually ordered streams into a jointly ordered one.
- Size the buffer from the lateness rather than guessing: 4,000 events per second times 30 seconds is 120,000 buffered events, and at 1 KB each about 120 MB of heap. That number is the real price of the ordering guarantee and belongs in front of whoever asked for it.
- Handle the idle partition explicitly, because it fails the feed rather than corrupting it: a partition with no traffic never advances its own maximum, so the watermark freezes and output stops entirely. Either every partition emits a periodic idle marker carrying the broker's current time, or the watermark falls back to wall clock for a partition silent beyond a threshold.
Follow-up
- The lateness budget is raised to five minutes. What is the new buffer, and what besides memory changes?
- The consumer restarts. Where does it resume from, and what does the feed look like for the first 30 seconds?
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?
Find version gaps and relay lag with window functions
outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.
Approach
- Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
- Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
- Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
- Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.
Follow-up
- Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
- Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?
Implement a rate limiter for an API endpoint, explaining the trade-offs between token bucket and sliding windo
Implement a rate limiter for an API endpoint, explaining the trade-offs between token bucket and sliding window log algorithms.
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 and implement an in-memory key-value store that supports basic operations along with time-based data ex
Design and implement an in-memory key-value store that supports basic operations along with time-based data expiration (TTL).
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 architect a highly scalable telemetry and logging pipeline to ingest millions of events per seco
How would you architect a highly scalable telemetry and logging pipeline to ingest millions of events per second with minimal 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 an asset-delivery CDN integration for a global user base, ensuring fast load times and reliable caching
Design an asset-delivery CDN integration for a global user base, ensuring fast load times and reliable caching policies.
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?
Describe how you would design a robust A/B testing infrastructure that allows dynamic configuration changes wi
Describe how you would design a robust A/B testing infrastructure that allows dynamic configuration changes without redeploying code.
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?
Every query on one table stalls for forty seconds mid-deploy
During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.
Approach
- Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
- Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
- Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
- Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.
Follow-up
- The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
- Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?
Built from the rounds and topics Relace candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Relace loop
- Write out the reported sequence: Recruiter Screen, Technical Screen, 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 Infrastructure Engineering
- Spend the session on Infrastructure Engineering, which Relace candidates report being tested on.
- Write one worked example in Infrastructure Engineering and time yourself on it.
Deliverable: One timed worked example in Infrastructure Engineering.
03Work Frontend Engineering
- Spend the session on Frontend Engineering, which Relace candidates report being tested on.
- Write one worked example in Frontend Engineering and time yourself on it.
Deliverable: One timed worked example in Frontend Engineering.
04Work Web Development
- Spend the session on Web Development, which Relace candidates report being tested on.
- Write one worked example in Web Development and time yourself on it.
Deliverable: One timed worked example in Web Development.
05Answer out loud: Coding & Algorithmic Problem Solving
- Answer aloud, timed: Implement a rate limiter for an API endpoint, explaining the trade-offs between token bucket and sliding window log algorithms.
- Answer aloud, timed: Given a list of dependency pairs, write a function to determine a valid build order, and identify if a circular dependency exists.
Deliverable: Spoken answers to 2 reported Coding & Algorithmic Problem Solving question(s), under time.
06Answer out loud: System Design & Architecture
- Answer aloud, timed: Design a real-time collaborative document editing system, focusing on conflict resolution strategies and data synchronization.
- Answer aloud, timed: How would you architect a highly scalable telemetry and logging pipeline to ingest millions of events per second with minimal latency?
Deliverable: Spoken answers to 2 reported System Design & Architecture question(s), under time.
07Answer out loud: Behavioral & Collaboration
- Answer aloud, timed: Describe a time when you had to make a significant technical trade-off to meet a tight product deadline. What was the outcome?
- Answer aloud, timed: How do you handle a situation where you disagree with a product manager or designer on how a feature should be implemented?
Deliverable: Spoken answers to 2 reported Behavioral & Collaboration 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.
Design a real-time collaborative document editing system, focusing on conflict resolution strategies and data
Design a real-time collaborative document editing system, focusing on conflict resolution strategies and data synchronization.
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 time when you had to make a significant technical trade-off to meet a tight product deadline. What
Describe a time when you had to make a significant technical trade-off to meet a tight product deadline. What was the outcome?
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 disagree with a product manager or designer on how a feature should be
How do you handle a situation where you disagree with a product manager or designer on how a feature should be implemented?
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 complex technical bug you encountered in production. How did you diagnose, mitigate, and preve
Tell me about a complex technical bug you encountered in production. How did you diagnose, mitigate, and 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?
Share an experience where you had to quickly learn a new technology or framework to deliver a critical project
Share an experience where you had to quickly learn a new technology or framework to deliver a critical project.
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
Design a real-time collaborative document editing system, focusing on conflict resolution strategies and data synchronization.
- 02
Describe a time when you had to make a significant technical trade-off to meet a tight product deadline. What was the outcome?
- 03
How do you handle a situation where you disagree with a product manager or designer on how a feature should be implemented?
- 04
Tell me about a complex technical bug you encountered in production. How did you diagnose, mitigate, and prevent it from happening again?
What is the hybrid work policy for Software Engineers at Relace?
Relace is headquartered in San Francisco, CA. We believe that high-bandwidth, in-person collaboration is incredibly valuable, especially for our tight-knit engineering team. Candidates should expect a hybrid schedule with regular collaborative days in our SF office.
Relace Software Engineer candidate reports ↗How long does the typical interview process take?
The entire process, from the initial recruiter screen to a final offer, typically takes between 2 to 4 weeks, depending on candidate availability and scheduling. We aim to keep the process moving quickly and respect your time.
Relace Software Engineer candidate reports ↗What technologies does the Relace engineering team use?
Our modern stack utilizes TypeScript, React, Node.js, Go, and PostgreSQL, all hosted on major cloud infrastructure. However, we value strong problem-solving skills and engineering fundamentals over specific language expertise.
Relace Software Engineer candidate reports ↗How should I prepare for the system design portion of the interview?
Focus on understanding core distributed systems concepts, data modeling, API design, and scalability trade-offs. Practice explaining how you would scale a system from its first thousand users to millions, detailing how you would handle bottlenecks and points of failure.
Relace Software Engineer candidate reports ↗What topics does Relace test in interviews?
Relace interviews most often cover Systems-level ML engineering, Infrastructure Engineering, Low-level performance optimization, Frontend Engineering, and CUDA. The exact emphasis depends on the specific role you apply for.
Relace 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.
- 01Relace 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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