As a Software Engineer at Spekit, you will build and scale the leading in-app learning and digital adoption platform. Spekit integrates directly into the SaaS applications that companies use every day—such as Salesforce, Slack, and custom web apps—delivering bite-sized, contextual knowledge to employees right when and where they need it. This requires solving complex engineering challenges around browser extension architecture, real-time data delivery, and seamless third-party integrations. In this role, your work directly impacts how hundreds of thousands of users learn and work. You will be responsible for developing robust APIs, optimizing frontend performance, and ensuring that the core platform remains highly available and lightning-fast. The engineering team at Spekit values pragmatic problem-solving, clean code, and a strong sense of product ownership. You will work on a collaborative, modern stack to build features that make complex software easy to use. This position is critical to Spekit's strategic growth. Because the platform must operate invisibly and efficiently across diverse client environments, you will tackle unique challenges in web security, DOM manipulation, and cross-origin communication. It is an inspiring environment for engineers who love building developer-friendly tooling, highly interactive user interfaces, and scalable backend infrastructure.
Introductory Chat
reportedInitial conversation with an Engineering Manager or VP of Engineering to align on background and expectations.
What to demonstrate
- Initial conversation with an Engineering Manager or VP of Engineering to align on background and expectations
- Depth in Full-Stack Development
How to prepare
- Answer aloud and timed: Walk us through the architectural choices you made in your take-home assignment. Why did you choose this specific state management pattern?
- Answer aloud and timed: How would you optimize the performance of a browser extension that needs to scan and manipulate the DOM of a heavy web application like Salesforce?
Take-Home Coding Challenge
reportedComplete a coding challenge by building a functional project, deploying it, and pushing the code to GitHub.
What to demonstrate
- Complete a coding challenge by building a functional project, deploying it, and pushing the code to GitHub
- Depth in Full-Stack Development
How to prepare
- Answer aloud and timed: Implement a function that handles API rate-limiting on the client side to ensure a smooth user experience.
- Answer aloud and timed: How do you handle cross-origin resource sharing (CORS) issues when building integrations that run across multiple external domains?
Collaborative Code Review
reportedParticipate in a code review session based on the take-home project submission.
What to demonstrate
- Participate in a code review session based on the take-home project submission
- Depth in Full-Stack Development
How to prepare
- Answer aloud and timed: How would you design a real-time notification system that pushes content updates to thousands of active browser extensions simultaneously?
- Answer aloud and timed: Design a scalable backend service that ingests, processes, and analyzes user engagement telemetry from third-party applications.
Live Pair Programming
reportedEngage in a live coding session to demonstrate coding skills and collaboration.
What to demonstrate
- Engage in a live coding session to demonstrate coding skills and collaboration
- Depth in Full-Stack Development
How to prepare
- Answer aloud and timed: How do you ensure data security and privacy when your application runs inside a customer's proprietary CRM environment?
- Answer aloud and timed: Tell me about a time you received critical feedback on a pull request or code submission. How did you handle it, and what did you learn?
Behavioral Round
reportedDiscuss behavioral aspects and cultural fit within the team.
What to demonstrate
- Discuss behavioral aspects and cultural fit within the team
- Depth in Full-Stack Development
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 round above and write down what you would ask to confirm before it.
Final Conversation
reportedMeet with the CTO or engineering leadership to discuss technical vision and team alignment.
What to demonstrate
- Meet with the CTO or engineering leadership to discuss technical vision and team alignment
- Depth in Full-Stack Development
How to prepare
- Work Full-Stack Development until you can explain it without notes
- Work Code Review until you can explain it without notes
PracHub editorial advice for the preparation topics above.
Deploy your take-home early
Do not wait until the last minute to deploy your project to a platform like Heroku or Vercel. Deployment issues can pop up unexpectedly, and having a live, working URL is a critical requirement of the assignment.
Write comprehensive tests
When submitting your take-home project, include clean unit or integration tests. This shows the team that you prioritize code quality and reliability, and it provides a great talking point during your code review session.
Be prepared to walk through your Git commit history during the code review
The engineers love to see clean, logical commits that show how you iteratively built your project over time.
Embrace constructive feedback
During your code review and pair programming sessions, the interviewers will suggest changes or point out potential issues. Do not get defensive. Instead, treat it as a collaborative brainstorming session, discuss the trade-offs, and show that you are easy to work with.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
How would you optimize the performance of a browser extension that needs to scan and manipulate the DOM of a h
How would you optimize the performance of a browser extension that needs to scan and manipulate the DOM of a heavy web application like Salesforce?
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 collaborate with product managers and designers to resolve an ambiguous
Describe a situation where you had to collaborate with product managers and designers to resolve an ambiguous product requirement.
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?
Explain why the owner filter ignores the listing index
The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.
Approach
- Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
- For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
- Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
- Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.
Follow-up
- 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
- A dashboard runs this for 40 owners in one page load. What changes about the design?
Stop tag and share joins from fanning out a page
resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.
Approach
- Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
- Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
- Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
- Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.
Follow-up
- The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
- A resource can be shared with the same user twice under different permissions. Does your count change, and should it?
Walk us through the architectural choices you made in your take-home assignment. Why did you choose this speci
Walk us through the architectural choices you made in your take-home assignment. Why did you choose this specific state management pattern?
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?
Implement a function that handles API rate-limiting on the client side to ensure a smooth user experience.
Implement a function that handles API rate-limiting on the client side to ensure a smooth user experience.
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?
How would you design a real-time notification system that pushes content updates to thousands of active browse
How would you design a real-time notification system that pushes content updates to thousands of active browser extensions 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 scalable backend service that ingests, processes, and analyzes user engagement telemetry from third-p
Design a scalable backend service that ingests, processes, and analyzes user engagement telemetry from third-party applications.
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 ensure data security and privacy when your application runs inside a customer's proprietary CRM env
How do you ensure data security and privacy when your application runs inside a customer's proprietary CRM environment?
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 Spekit candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Spekit loop
- Write out the reported sequence: Introductory Chat, Take-Home Coding Challenge, Collaborative Code Review, Live Pair Programming, Behavioral Round, Final Conversation.
- 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 6 reported rounds, with the weakest marked.
02Work Full-Stack Development
- Spend the session on Full-Stack Development, which Spekit candidates report being tested on.
- Write one worked example in Full-Stack Development and time yourself on it.
Deliverable: One timed worked example in Full-Stack Development.
03Work Code Review
- Spend the session on Code Review, which Spekit candidates report being tested on.
- Write one worked example in Code Review and time yourself on it.
Deliverable: One timed worked example in Code Review.
04Work Take-Home Assignments
- Spend the session on Take-Home Assignments, which Spekit candidates report being tested on.
- Write one worked example in Take-Home Assignments and time yourself on it.
Deliverable: One timed worked example in Take-Home Assignments.
05Answer out loud: Technical & Practical Coding
- Answer aloud, timed: Walk us through the architectural choices you made in your take-home assignment. Why did you choose this specific state management pattern?
- Answer aloud, timed: How would you optimize the performance of a browser extension that needs to scan and manipulate the DOM of a heavy web application like Salesforce?
Deliverable: Spoken answers to 2 reported Technical & Practical Coding question(s), under time.
06Answer out loud: System Design & Architecture
- Answer aloud, timed: How would you design a real-time notification system that pushes content updates to thousands of active browser extensions simultaneously?
- Answer aloud, timed: Design a scalable backend service that ingests, processes, and analyzes user engagement telemetry from third-party applications.
Deliverable: Spoken answers to 2 reported System Design & Architecture question(s), under time.
07Answer out loud: Behavioral & Collaboration
- Answer aloud, timed: Tell me about a time you received critical feedback on a pull request or code submission. How did you handle it, and what did you learn?
- Answer aloud, timed: Describe a situation where you had to collaborate with product managers and designers to resolve an ambiguous product requirement.
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.
How do you handle cross-origin resource sharing (CORS) issues when building integrations that run across multi
How do you handle cross-origin resource sharing (CORS) issues when building integrations that run across multiple external domains?
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 received critical feedback on a pull request or code submission. How did you handle i
Tell me about a time you received critical feedback on a pull request or code submission. How did you handle it, and what did you learn?
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 balance the need to deliver features quickly with the responsibility of maintaining code quality an
How do you balance the need to deliver features quickly with the responsibility of maintaining code quality and reducing technical debt?
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 cross-origin resource sharing (CORS) issues when building integrations that run across multiple external domains?
- 02
Tell me about a time you received critical feedback on a pull request or code submission. How did you handle it, and what did you learn?
- 03
How do you balance the need to deliver features quickly with the responsibility of maintaining code quality and reducing technical debt?
How difficult is the Spekit technical interview process?
The process is of average difficulty but highly practical. Rather than testing you on obscure algorithmic brainteasers, Spekit focuses heavily on real-world coding, deployment, and collaborative code reviews. If you are comfortable building and deploying full-stack web applications, you will find the process highly relevant.
Spekit Software Engineer candidate reports ↗What is the expectation for the take-home assignment?
You are expected to build a fully functional application or feature based on a prompt, push the code to a public GitHub repository, and deploy it to a live cloud environment. The team evaluates code quality, repository organization, test coverage, and how well you handle edge cases.
Spekit Software Engineer candidate reports ↗How long does the entire interview process typically take?
The process generally takes between two to four weeks, depending on candidate scheduling and team availability. Spekit is known for keeping candidates informed and maintaining structured, well-communicated steps throughout the loop.
Spekit Software Engineer candidate reports ↗Does Spekit offer remote or hybrid work options for engineers?
Yes, Spekit is a remote-first organization with a highly distributed engineering team. They have hubs in various locations, but they are fully equipped to support, onboard, and collaborate with engineers working remotely across multiple time zones.
Spekit Software Engineer candidate reports ↗What topics does Spekit test in interviews?
Spekit interviews most often cover Account Executive (AE) role responsibilities, Full-Stack Development, Product understanding (domain knowledge), Code Review, and Take-Home Assignments. The exact emphasis depends on the specific role you apply for.
Spekit 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.
- 01Spekit 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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