At Novel Engineering, the Software Engineer role is central to the development of advanced aerospace, defense, and embedded systems. You will function as a key contributor in a highly collaborative environment, working alongside electrical, mechanical, and systems engineers to build mission-critical software stacks. This position is not just about writing code; it is about applying rigorous engineering principles to solve complex, real-world problems that directly impact aerospace and control systems. You will be expected to take ownership of technical decisions and deliverables, ensuring that your work meets the high standards required for mission-critical software. Whether you are developing novel algorithm implementations in C#, working on embedded C/C++ systems, or supporting rapid prototyping cycles, your contributions will have a tangible impact on the company’s ability to deliver reliable, high-performance solutions. This role demands a balance of technical depth, engineering discipline, and the ability to thrive in a fast-paced, on-site environment.
Application Review
reportedInitial review of your application to assess qualifications and fit for the role.
What to demonstrate
- Initial review of your application to assess qualifications and fit for the role
- Depth in C#
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.
Onsite Interview
reportedRigorous assessment conducted on-site to evaluate technical aptitude and problem-solving skills.
What to demonstrate
- Rigorous assessment conducted on-site to evaluate technical aptitude and problem-solving skills
- Depth in C#
How to prepare
- Answer aloud and timed: How do you ensure your code meets the standards for mission-critical or zero-trust environments?
- Answer aloud and timed: What considerations do you prioritize when working with low-level systems or RTOS environments?
PracHub editorial advice for the preparation topics above.
Structure your answers
When answering behavioral or process-based questions, use the STAR method (Situation, Task, Action, Result) to keep your responses clear and impact-focused.
Show your work
When solving technical problems on a whiteboard or screen, verbalize your thought process. Interviewers are as interested in your problem-solving methodology as they are in the final solution.
Know your resume
Be prepared to dive deep into every project you list. You should be able to explain the "why" behind your technical decisions.
Understand the domain
Familiarize yourself with the challenges of aerospace and embedded systems. Showing an interest in the specific mission of Novel Engineering goes a long way.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
How do you approach the design of an algorithm for a complex, constrained system?
How do you approach the design of an algorithm for a complex, constrained system?
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?
Can you walk me through your process for diagnosing and fixing a bug in an existing, large-scale codebase?
Can you walk me through your process for diagnosing and fixing a bug in an existing, large-scale codebase?
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?
How do you ensure your code meets the standards for mission-critical or zero-trust environments?
How do you ensure your code meets the standards for mission-critical or zero-trust environments?
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?
What considerations do you prioritize when working with low-level systems or RTOS environments?
What considerations do you prioritize when working with low-level systems or RTOS environments?
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?
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?
How do you approach the peer review process, both as a reviewer and as the author of the code?
How do you approach the peer review process, both as a reviewer and as the author of the code?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How do you balance the need for rapid prototyping with the requirement for robust, maintainable documentation?
How do you balance the need for rapid prototyping with the requirement for robust, maintainable documentation?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
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 Novel Engineering candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Novel Engineering loop
- Write out the reported sequence: Application Review, Onsite 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 2 reported rounds, with the weakest marked.
02Work C#
- Spend the session on C#, which Novel Engineering candidates report being tested on.
- Write one worked example in C# and time yourself on it.
Deliverable: One timed worked example in C#.
03Work C/C++
- Spend the session on C/C++, which Novel Engineering candidates report being tested on.
- Write one worked example in C/C++ and time yourself on it.
Deliverable: One timed worked example in C/C++.
04Work Embedded systems software
- Spend the session on Embedded systems software, which Novel Engineering candidates report being tested on.
- Write one worked example in Embedded systems software and time yourself on it.
Deliverable: One timed worked example in Embedded systems software.
05Answer out loud: Technical & Algorithm Design
- Answer aloud, timed: How do you approach the design of an algorithm for a complex, constrained system?
- Answer aloud, timed: Can you walk me through your process for diagnosing and fixing a bug in an existing, large-scale codebase?
Deliverable: Spoken answers to 2 reported Technical & Algorithm Design question(s), under time.
06Answer out loud: Engineering Process & Collaboration
- Answer aloud, timed: Describe a time you had to collaborate with non-software engineers (e.g., mechanical or electrical) to solve a system-level issue.
- Answer aloud, timed: How do you approach the peer review process, both as a reviewer and as the author of the code?
Deliverable: Spoken answers to 2 reported Engineering Process & Collaboration question(s), under time.
07Dry run for Novel Engineering
- Run one full mock under time, then write down the two questions you most want to ask your interviewers.
Deliverable: A completed timed mock and two questions to ask.
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.
Describe a time you had to collaborate with non-software engineers (e.g., mechanical or electrical) to solve a
Describe a time you had to collaborate with non-software engineers (e.g., mechanical or electrical) to solve a system-level issue.
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?
Explain your experience with Agile methodologies and how you contribute to sprint planning and story creation.
Explain your experience with Agile methodologies and how you contribute to sprint planning and story creation.
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?
Ship under a deadline and bound the debt you chose
You have four days to ship a tenant-facing listing endpoint. The version you would defend uses keyset pagination over (tenant_id, status, updated_at DESC, resource_id DESC); the version you can finish uses LIMIT/OFFSET with no matching index. Describe a deadline call you actually made of this shape: what you shipped, what you knowingly deferred, how you bounded the damage with a mechanism rather than an intention, and the specific numeric condition that would force the follow-up. Name who you told and where you wrote it down.
Approach
- Name the deferred failure precisely instead of calling it slow. OFFSET n makes the database produce and discard n rows, so cost grows with page depth; without an index matching the sort, every matching row is read and sorted before the limit applies; and rows inserted between two page fetches shift across the boundary so items are skipped or repeated with nothing in the response to signal it.
- Bound the blast radius with something mechanical rather than a promise: cap maximum page depth, cap page size, restrict the endpoint to one internal caller, or keep it behind a flag. State which failure each cap removes and which it leaves standing.
- Attach a number to the trigger and wire it to an alarm: the first tenant crossing N resources, or the endpoint's p99 crossing its share of the 400 ms budget, so the debt announces itself instead of waiting to be remembered.
- Write it where the next engineer looks, which is the code and the ticket, not a chat message: what was deferred, why, the cap, and the trigger.
Follow-up
- At what page depth does the offset version breach your latency budget, given your page size and row counts?
- What breaks first when you switch to keyset pagination later, and what does a client holding an old page token see?
- 01
Describe a time you had to collaborate with non-software engineers (e.g., mechanical or electrical) to solve a system-level issue.
- 02
Explain your experience with Agile methodologies and how you contribute to sprint planning and story creation.
- 03
You have four days to ship a tenant-facing listing endpoint. The version you would defend uses keyset pagination over (tenant_id, status, updated_at DESC, resource_id DESC); the version you can finish uses LIMIT/OFFSET with no matching index. Describe a deadline call you actually made of this shape: what you shipped, what you knowingly deferred, how you bounded the damage with a mechanism rather than an intention, and the specific numeric condition that would force the follow-up. Name who you told and where you wrote it down.
How long does the interview process typically take?
While timelines can vary, the process is designed to be efficient. From the initial screen to the final decision, you can expect a professional and relatively fast-paced experience.
Novel Engineering Software Engineer candidate reports ↗Is there a remote work option?
No, all Software Engineer roles at Novel Engineering are strictly on-site in Melbourne, FL.
Novel Engineering Software Engineer candidate reports ↗What differentiates a top-tier candidate?
Beyond technical skills, we look for engineers who take initiative, value ownership, and can effectively communicate complex ideas to a multidisciplinary team. Demonstrating a disciplined approach to the SDLC is a major differentiator.
Novel Engineering Software Engineer candidate reports ↗How much should I prepare for coding questions?
Expect to be tested on your ability to design and implement algorithms. Focus on writing clean, maintainable code rather than just memorizing syntax.
Novel Engineering Software Engineer candidate reports ↗What topics does Novel Engineering test in interviews?
Novel Engineering interviews most often cover C#, C/C++, Embedded systems software, Algorithm development, and Software Development Lifecycle (SDLC). The exact emphasis depends on the specific role you apply for.
Novel Engineering 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.
- 01Novel Engineering 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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