At Quantum Computing Inc. (QCi), the Software Engineer role is a highly specialized position that bridges the gap between state-of-the-art quantum optics hardware and modern software ecosystems. Unlike typical enterprise software development, engineering at QCi involves writing software that directly interacts with room-temperature, low-power integrated photonics and quantum machines. You will play a crucial role in making quantum computing, advanced sensing, and cybersecurity technologies accessible and performant for real-world applications. The software you design and build acts as the central nervous system for QCi’s hardware products. Your primary impact lies in creating the low-latency communication layers, robust APIs, and comprehensive client SDKs that hardware, firmware, and systems teams rely on to control, test, and automate these advanced optical systems. This is a highly cross-functional environment where your code directly affects physical hardware, making the work both intellectually challenging and deeply rewarding. To succeed in this role, you must thrive in a high-autonomy startup environment. You will be expected to take full ownership of your systems, collaborate closely with physicists and hardware engineers, and write exceptionally clean, performant, and reliable code in both and. C++ Python
Technical Recruiter Screen
reportedInitial screening by a technical recruiter to assess basic qualifications.
What to demonstrate
- Initial screening by a technical recruiter to assess basic qualifications
- Depth in C++ (C++11 or later)
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 Phone Interview
reportedDeep-dive interview focusing on systems programming and hardware-software integration.
What to demonstrate
- Deep-dive interview focusing on systems programming and hardware-software integration
- Depth in C++ (C++11 or later)
How to prepare
- Answer aloud and timed: Describe how virtual functions and the vtable work in C++. What is the runtime cost of dynamic dispatch, and how can you avoid it in performance-critical loops?
- Answer aloud and timed: How do you detect and prevent memory leaks and dangling pointers in a long-running backend service?
Virtual Onsite Interview
reportedComprehensive interview consisting of several panel sessions covering coding, system design, and behavioral scenarios.
What to demonstrate
- Comprehensive interview consisting of several panel sessions covering coding, system design, and behavioral scenarios
- Depth in C++ (C++11 or later)
How to prepare
- Answer aloud and timed: What are move semantics and rvalue references? How do they help optimize memory allocation in low-latency systems?
- Answer aloud and timed: If you are receiving data from a hardware device over UART or SPI, how do you handle packet framing, checksum validation, and buffer overflows?
PracHub editorial advice for the preparation topics above.
You do not need a PhD in quantum physics to succeed in this role
QCi is looking for solid systems software engineers who are curious about hardware and eager to learn the physics domain on the job.
Emphasize Hardware Curiosity
Even if your background is purely in classic systems software, show a strong interest in learning how the physical photonics hardware operates. Ask questions about how the optical systems are calibrated and controlled.
Focus on Clean API Boundaries
When designing systems, always prioritize clean separation of concerns. Show how you separate low-level hardware communication logic from high-level business logic and client APIs.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Explain the difference between `std::unique_ptr` and `std::shared_ptr` in C++11, and describe the performance
Explain the difference between std::unique_ptr and std::shared_ptr in C++11, and describe the performance overhead associated with each.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
How would you design a thread-safe, lock-free queue in C++ for passing data between a high-speed hardware read
How would you design a thread-safe, lock-free queue in C++ for passing data between a high-speed hardware reader thread and a processing thread?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Describe how virtual functions and the vtable work in C++. What is the runtime cost of dynamic dispatch, and h
Describe how virtual functions and the vtable work in C++. What is the runtime cost of dynamic dispatch, and how can you avoid it in performance-critical loops?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
How do you detect and prevent memory leaks and dangling pointers in a long-running backend service?
How do you detect and prevent memory leaks and dangling pointers in a long-running backend service?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
What are move semantics and rvalue references? How do they help optimize memory allocation in low-latency syst
What are move semantics and rvalue references? How do they help optimize memory allocation in low-latency systems?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
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?
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?
What are the primary differences between gRPC and REST APIs when designing interfaces for hardware control, an
What are the primary differences between gRPC and REST APIs when designing interfaces for hardware control, and when would you choose one over the other?
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 implement a robust retry mechanism and state machine to handle transient connection drops betwee
How would you implement a robust retry mechanism and state machine to handle transient connection drops between a backend service and an embedded controller?
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 would you design a software abstraction layer that supports multiple hardware revisions without breaking c
How would you design a software abstraction layer that supports multiple hardware revisions without breaking client-facing APIs?
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 design a Python-based test framework to automate the calibration of an optical sensor?
How would you design a Python-based test framework to automate the calibration of an optical sensor?
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 write a Python wrapper around a performance-critical C++ library (e.g., using ctypes, c
Describe how you would write a Python wrapper around a performance-critical C++ library (e.g., using ctypes, cffi, or pybind11).
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 structure a command-line interface (CLI) tool in Python to allow hardware engineers to easily run d
How do you structure a command-line interface (CLI) tool in Python to allow hardware engineers to easily run diagnostics and log system telemetry?
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?
Explain how you would implement a distributed logging system to capture and correlate errors across both the h
Explain how you would implement a distributed logging system to capture and correlate errors across both the hardware controller and the cloud backend.
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 that your automated validation scripts run reliably in a continuous integration (CI) pipelin
How do you ensure that your automated validation scripts run reliably in a continuous integration (CI) pipeline connected to physical hardware testbeds?
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?
One log partition stops advancing while the others drain
Search results for a subset of tenants are hours stale; the rest are current. The projection consumer reports lag of zero on 15 of 16 partitions and 400,000 on one. Its error rate is flat and its CPU is idle. outbox_event has no pending rows older than a second, so the relay has published everything it holds. Identify the mechanism, give the ordered checks, and state what you do in the first ten minutes versus what you change permanently.
Approach
- Read the lag distribution first. A slow consumer lags everywhere; zero on fifteen partitions and 400,000 on one is not throughput. Idle CPU on the stuck partition means the consumer is not advancing its offset at all, which points at one message it cannot get past rather than at a rate problem.
- Exonerate the producer before touching the consumer. No pending outbox rows older than a second means the relay published, so the event exists in the log. This separates never sent from sent and never applied, which are different code paths and usually different owners.
- Read the message at the stuck offset and the handler's log lines for its event_id. A flat error rate with no progress has two explanations and you must distinguish them: the handler is throwing and the retry loop is swallowing it, or the handler is blocking on something and never returning. Idle CPU with no error lines favours the second.
- Mitigate before diagnosing further. Move the offending event to a dead-letter store and commit the offset past it. Adding consumers does nothing here, because a partition is consumed by exactly one member of the group, and the blast radius is every aggregate hashed to that partition, not only the aggregate that produced the bad event.
Follow-up
- The dead-lettered event carried aggregate_version 7 and the projection had applied 6. What must the replay do differently if 8 and 9 landed in the meantime?
- How do you show staleness to the user while the partition is behind, given the API already returns the projection's watermark?
Built from the rounds and topics Quantum Computing candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Quantum Computing loop
- Write out the reported sequence: Technical Recruiter Screen, Technical Phone Interview, Virtual 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 3 reported rounds, with the weakest marked.
02Work C++ (C++11 or later)
- Spend the session on C++ (C++11 or later), which Quantum Computing candidates report being tested on.
- Write one worked example in C++ (C++11 or later) and time yourself on it.
Deliverable: One timed worked example in C++ (C++11 or later).
03Work Python
- Spend the session on Python, which Quantum Computing candidates report being tested on.
- Write one worked example in Python and time yourself on it.
Deliverable: One timed worked example in Python.
04Work Backend Systems Engineering
- Spend the session on Backend Systems Engineering, which Quantum Computing candidates report being tested on.
- Write one worked example in Backend Systems Engineering and time yourself on it.
Deliverable: One timed worked example in Backend Systems Engineering.
05Answer out loud: Systems Programming & Low-Latency C++
- Answer aloud, timed: Explain the difference between `std::unique_ptr` and `std::shared_ptr` in C++11, and describe the performance overhead associated with each.
- Answer aloud, timed: How would you design a thread-safe, lock-free queue in C++ for passing data between a high-speed hardware reader thread and a processing thread?
Deliverable: Spoken answers to 2 reported Systems Programming & Low-Latency C++ question(s), under time.
06Answer out loud: Hardware Interfacing & Communication Protocols
- Answer aloud, timed: If you are receiving data from a hardware device over UART or SPI, how do you handle packet framing, checksum validation, and buffer overflows?
- Answer aloud, timed: What are the primary differences between gRPC and REST APIs when designing interfaces for hardware control, and when would you choose one over the other?
Deliverable: Spoken answers to 2 reported Hardware Interfacing & Communication Protocols question(s), under time.
07Answer out loud: Python Tooling, Test Automation & Diagnostics
- Answer aloud, timed: How would you design a Python-based test framework to automate the calibration of an optical sensor?
- Answer aloud, timed: Describe how you would write a Python wrapper around a performance-critical C++ library (e.g., using ctypes, cffi, or pybind11).
Deliverable: Spoken answers to 2 reported Python Tooling, Test Automation & Diagnostics 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.
If you are receiving data from a hardware device over UART or SPI, how do you handle packet framing, checksum
If you are receiving data from a hardware device over UART or SPI, how do you handle packet framing, checksum validation, and buffer overflows?
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 your experience with socket programming. How do you handle non-blocking I/O and multiplexing (e.g., u
Describe your experience with socket programming. How do you handle non-blocking I/O and multiplexing (e.g., using select or epoll)?
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 work with a hardware or firmware engineer to debug an issue where it wasn't cl
Describe a time when you had to work with a hardware or firmware engineer to debug an issue where it wasn't clear if the bug was in the software or the physical hardware.
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 prioritize your tasks and maintain high productivity when working in a startup environment with shi
How do you prioritize your tasks and maintain high productivity when working in a startup environment with shifting requirements and high autonomy?
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 when you had to explain a complex software architecture decision to a non-technical stake
Tell me about a time when you had to explain a complex software architecture decision to a non-technical stakeholder or a physicist who did not have a software background.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Give an example of a project where you took complete ownership from initial requirements gathering to final de
Give an example of a project where you took complete ownership from initial requirements gathering to final deployment. What challenges did you face, and how did you overcome them?
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
If you are receiving data from a hardware device over UART or SPI, how do you handle packet framing, checksum validation, and buffer overflows?
- 02
Describe your experience with socket programming. How do you handle non-blocking I/O and multiplexing (e.g., using `select` or `epoll`)?
- 03
Describe a time when you had to work with a hardware or firmware engineer to debug an issue where it wasn't clear if the bug was in the software or the physical hardware.
- 04
How do you prioritize your tasks and maintain high productivity when working in a startup environment with shifting requirements and high autonomy?
What is the hybrid/remote work policy for this role?
The role is based in Hoboken, NJ. Because this position involves close collaboration with hardware engineering teams and requires direct access to physical quantum optics hardware, candidates should expect a regular onsite presence at the Hoboken facility.
Quantum Computing Software Engineer candidate reports ↗Do I need a background in quantum mechanics or physics to be hired?
No. While a background in physics or optical engineering is a plus, QCi is primarily looking for exceptional systems software engineers. The hardware teams will provide the domain-specific physics knowledge; your job is to write the robust, performant software that controls and automates those physical systems.
Quantum Computing Software Engineer candidate reports ↗How is the work-life balance in QCi's startup environment?
QCi values work-life balance and understands that personal priorities are important. However, because the environment is highly collaborative and cross-functional, team members must effectively balance their personal schedules with team objectives to ensure project milestones are met.
Quantum Computing Software Engineer candidate reports ↗What differentiates successful candidates during the interview process?
Successful candidates demonstrate strong technical curiosity and a willingness to learn about hardware constraints. They don't just write clean code; they think deeply about edge cases, hardware failures, latency, and how their software design choices impact the physical systems and the engineers who use them.
Quantum Computing Software Engineer candidate reports ↗What topics does Quantum Computing test in interviews?
Quantum Computing interviews most often cover C++ (C++11 or later), New Business Development, Software Quality Assurance (QA), Python, and Test Engineering. The exact emphasis depends on the specific role you apply for.
Quantum Computing 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.
- 01Quantum Computing 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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