A Software Engineer at Higharc is responsible for building and scaling the world's first web-based 3D platform for homebuilding. This is not a typical web application development role; it sits at the intersection of cloud computing, computational geometry, and real-time 3D graphics. You will contribute to a complex, proprietary engine that automates architectural design, structural engineering, and estimation, replacing legacy desktop CAD software with a modern, collaborative web application. The impact of this role is massive. By writing high-performance code that runs directly in the browser, you enable homebuilders to design, customize, and generate permit-ready blueprints in minutes instead of weeks. The technical challenges you will solve involve complex data structures, spatial relationships, and procedural generation, making this position highly critical to Higharc's mission of transforming a multi-trillion-dollar industry. Whether you join the Studio, Geometric Modeling/CAD, Config, or team, you will work on a highly collaborative, remote-first team of experts. You will tackle problems that require deep analytical thinking, clean architectural design, and a strong appreciation for user experience, as our tools are used by architectural designers, sales teams, and homebuyers alike. RTB (Real-Time Building)
Recruiter Call
reportedInitial conversation with a recruiter to discuss your background, career goals, and compensation expectations.
What to demonstrate
- Initial conversation with a recruiter to discuss your background, career goals, and compensation expectations
- Depth in CAD (Computer-Aided 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 Conversation
reportedDeep-dive technical discussion with the hiring manager, focusing on previous work and technical achievements.
What to demonstrate
- Deep-dive technical discussion with the hiring manager
- Focusing on previous work and technical achievements
How to prepare
- Answer aloud and timed: Describe the data structures you would use to represent a 3D house model that supports real-time editing and parametric constraints.
- Answer aloud and timed: How would you optimize a collision detection system for hundreds of architectural objects in a web browser?
Take-Home Challenge
reportedComplete a take-home challenge tailored to your specific domain, emphasizing clean, production-grade code.
What to demonstrate
- Complete a take-home challenge tailored to your specific domain, emphasizing clean, production-grade code
- Depth in CAD (Computer-Aided Design)
How to prepare
- Answer aloud and timed: Walk through the process of generating a clean 2D floor plan layout from a 3D spatial database.
- Answer aloud and timed: How do you optimize rendering performance in a web-based 3D environment using WebGL or Three.js?
Code Review Interview
reportedParticipate in a follow-up interview to walk the team through your implementation and discuss design choices.
What to demonstrate
- Participate in a follow-up interview to walk the team through your implementation and discuss design choices
- Depth in CAD (Computer-Aided Design)
How to prepare
- Answer aloud and timed: Describe how you would design a synchronization protocol for a collaborative, multi-user CAD editor.
- Answer aloud and timed: What strategies would you use to manage state in a highly interactive, visual application with deeply nested components?
PracHub editorial advice for the preparation topics above.
Focus on the fundamentals
Brush up on your linear algebra, vector math, and basic computational geometry algorithms. Even if you aren't a graphics specialist, having a strong grasp of spatial reasoning is highly valuable across all our engineering teams.
Treat the code review as a pairing session
During the follow-up code review, our engineers want to see what it is like to work with you. Be open to feedback, explain your thought process clearly, and collaborate on finding the best solutions to any extensions we discuss.
Hardcoding to the sample inputs
Solve the stated problem rather than the two examples; special-casing a literal to make a sample pass is obvious immediately and reads as either a misunderstanding or an attempt to fake progress. If you genuinely cannot generalise yet, say which part is a stub and what would replace it.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Explain how you would determine if a given 2D point lies inside a complex, non-convex polygon.
Explain how you would determine if a given 2D point lies inside a complex, non-convex polygon.
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 the data structures you would use to represent a 3D house model that supports real-time editing and p
Describe the data structures you would use to represent a 3D house model that supports real-time editing and parametric constraints.
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?
Walk through the process of generating a clean 2D floor plan layout from a 3D spatial database.
Walk through the process of generating a clean 2D floor plan layout from a 3D spatial database.
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?
Talk about a highly ambiguous technical problem you solved. How did you define the requirements and execute th
Talk about a highly ambiguous technical problem you solved. How did you define the requirements and execute the 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?
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?
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?
How would you optimize a collision detection system for hundreds of architectural objects in a web browser?
How would you optimize a collision detection system for hundreds of architectural objects in a web browser?
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 optimize rendering performance in a web-based 3D environment using WebGL or Three.js?
How do you optimize rendering performance in a web-based 3D environment using WebGL or Three.js?
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 synchronization protocol for a collaborative, multi-user CAD editor.
Describe how you would design a synchronization protocol for a collaborative, multi-user CAD editor.
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?
What strategies would you use to manage state in a highly interactive, visual application with deeply nested c
What strategies would you use to manage state in a highly interactive, visual application with deeply nested components?
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 architect a system to handle large file imports and exports (such as DXF, IFC, or OBJ) without bloc
How do you architect a system to handle large file imports and exports (such as DXF, IFC, or OBJ) without blocking the main browser thread?
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 decouple the geometric computation engine from the rendering layer to ensure modularity.
Explain how you would decouple the geometric computation engine from the rendering layer to ensure modularity.
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?
Read latency spikes on a sixty-second sawtooth
The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.
Approach
- Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
- Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
- Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
- De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.
Follow-up
- The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
- How does your answer change if the recompute takes 4 seconds instead of 250 ms?
Built from the rounds and topics Higharc candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Higharc loop
- Write out the reported sequence: Recruiter Call, Technical Conversation, Take-Home Challenge, Code Review Interview.
- 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 4 reported rounds, with the weakest marked.
02Work CAD (Computer-Aided Design)
- Spend the session on CAD (Computer-Aided Design), which Higharc candidates report being tested on.
- Write one worked example in CAD (Computer-Aided Design) and time yourself on it.
Deliverable: One timed worked example in CAD (Computer-Aided Design).
03Work Geometry
- Spend the session on Geometry, which Higharc candidates report being tested on.
- Write one worked example in Geometry and time yourself on it.
Deliverable: One timed worked example in Geometry.
04Work Geometric Modeling
- Spend the session on Geometric Modeling, which Higharc candidates report being tested on.
- Write one worked example in Geometric Modeling and time yourself on it.
Deliverable: One timed worked example in Geometric Modeling.
05Answer out loud: Geometric Modeling & CAD Algorithms
- Answer aloud, timed: Explain how you would determine if a given 2D point lies inside a complex, non-convex polygon.
- Answer aloud, timed: How do you handle floating-point precision issues when performing geometric calculations like line intersections?
Deliverable: Spoken answers to 2 reported Geometric Modeling & CAD Algorithms question(s), under time.
06Answer out loud: System Architecture & Web Graphics
- Answer aloud, timed: How do you optimize rendering performance in a web-based 3D environment using WebGL or Three.js?
- Answer aloud, timed: Describe how you would design a synchronization protocol for a collaborative, multi-user CAD editor.
Deliverable: Spoken answers to 2 reported System Architecture & Web Graphics question(s), under time.
07Answer out loud: Behavioral & Startup Culture
- Answer aloud, timed: Describe a time when you had to make a technical trade-off to meet a tight product deadline.
- Answer aloud, timed: How do you approach a situation where you disagree with a product manager's specification or a peer's architectural decision?
Deliverable: Spoken answers to 2 reported Behavioral & Startup Culture 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 floating-point precision issues when performing geometric calculations like line intersectio
How do you handle floating-point precision issues when performing geometric calculations like line intersections?
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 technical trade-off to meet a tight product deadline.
Describe a time when you had to make a technical trade-off to meet a tight product 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 approach a situation where you disagree with a product manager's specification or a peer's architec
How do you approach a situation where you disagree with a product manager's specification or a peer's architectural decision?
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 constructive criticism during a rigorous, hands-on code review session?
How do you handle constructive criticism during a rigorous, hands-on code review session?
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?
Why are you interested in working on homebuilding and CAD technology, and how do you stay updated with industr
Why are you interested in working on homebuilding and CAD technology, and how do you stay updated with industry trends?
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 floating-point precision issues when performing geometric calculations like line intersections?
- 02
Describe a time when you had to make a technical trade-off to meet a tight product deadline.
- 03
How do you approach a situation where you disagree with a product manager's specification or a peer's architectural decision?
- 04
How do you handle constructive criticism during a rigorous, hands-on code review session?
How difficult is the Higharc interview process?
The process is rated as highly challenging and rigorous. Because we build a web-based CAD engine, we test for deep technical fundamentals, spatial reasoning, and clean coding practices rather than standard, memorized interview questions.
Higharc Software Engineer candidate reports ↗How long does the entire interview process take?
The typical timeline from the initial recruiter screen to a final decision is approximately 3 to 4 weeks, depending on your availability to complete the take-home challenge.
Higharc Software Engineer candidate reports ↗Is Higharc a fully remote company?
Yes, Higharc is a remote-first company. We have built a highly collaborative, distributed team across North America, utilizing modern communication tools to stay aligned and connected.
Higharc Software Engineer candidate reports ↗What is the expectation for the take-home challenge?
We expect production-grade code. This means your submission should be clean, well-structured, thoroughly tested, and accompanied by clear documentation explaining your technical choices and trade-offs.
Higharc Software Engineer candidate reports ↗What topics does Higharc test in interviews?
Higharc interviews most often cover Cross-functional Collaboration, Requirements Gathering, Engineering Management, VDC (Virtual Design & Construction), and Presentation Skills. The exact emphasis depends on the specific role you apply for.
Higharc 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.
- 01Higharc 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
Explore related engineering environments and compare the preparation focus.
Cognition Software Engineer Interview Guide
What Cognition asks Software Engineer candidates, from reported rounds and questions.
Discord Software Engineer Interview Guide
Database practice for Discord candidates: how an index changes a query plan, and which anomalies survive a given isolation level, since read committed still permits non-repeatable reads.
CoreWeave Software Engineer Interview Guide
Failure-handling practice for CoreWeave software engineer candidates: requests whose outcome a timeout leaves unknown, where a retry is safe, and deduplicating at the receiver instead of assuming exactly-once delivery.
Aerospike Software Engineer Interview Questions & Guide 2026
Aerospike database-engine preparation through an original single-owner Python key-value store with bounded logical index accounting, disk-offset reads, conditional writes, tombstones, process-restart recovery and 3,240 checks. Existing 14 p