What to expect
Prepare for a Harvey Software Engineer conversation by connecting technical fundamentals to document traceability and bounded inference. This guide gives you six focused practice questions, an illustrated design exercise and a study plan with concrete outputs. Use it to build answers you can explain and test, then adjust the emphasis to the actual team and assessment.
Harvey's official company resource provides background on AI tools for legal and professional work. That context helps you ask better questions about users and product constraints. It does not establish a required interview language, a fixed sequence of rounds or a promised set of questions.
Explore six guide-only practice questions →
Build a role brief before you study
A useful starting question for this domain is how a team would detect and recover from a document result being attributed to the wrong source passage. Write down who is affected, what they should be able to trust and which component owns the accepted state. This is an original practice scenario, not a description of Harvey's internal architecture.
Read the vacancy with three columns in your notes: a stated requirement, an example from your work that demonstrates it, and an uncertainty to ask about. Separate an explicit language or framework requirement from a tool you happen to prefer. If the role is mainly frontend, focus on state, accessibility and browser behavior; if it is infrastructure-oriented, bring deeper evidence about concurrency, failure recovery and operation under load.
Ask the recruiter which assessments apply, whether work is live or take-home, what tools are permitted and how seniority changes the expected depth. Make those answers change your preparation. A timed coding discussion calls for a different rehearsal from a project review or a collaborative debugging session.
Choose your first practice session
Begin with minimum concurrent machines, implement a bounded retry helper, build a rate limiter. Read each prompt without its answer, state the contract aloud and attempt a solution before checking the approach. The follow-ups are designed to expose assumptions, so write the changed requirement before changing your implementation.
For a coding task, retain one small example with expected output. For a design task, draw the state owner and one failure boundary. For a project question, identify your own decision and the evidence behind it. These artifacts make gaps visible much faster than rereading an explanation you already recognize.
Guide-only practice question bank
These six practice topics are selected from the published third-party guide. PracHub supplies the clarified problem statements, solution approaches and follow-ups. Treat them as preparation material; their inclusion does not independently verify that this employer asked them.
Minimum concurrent machines
Practice prompt: Given task start and end times, find the minimum number of machines needed when each task occupies one machine for its entire interval.
Solution approach:
- Treat intervals as half-open so a machine can be reused when one task ends exactly as another starts. Sort start and end events, processing ends before starts at equal times.
- Maintain the active count and its maximum. Sorting costs O(n log n); the scan is linear. A min-heap of end times is another useful implementation.
- Test non-overlapping tasks, all-overlapping tasks, tied boundaries and invalid intervals. Decide whether zero-length tasks consume capacity before calculating.
Follow-up: How would you return an assignment of tasks to machine IDs as well as the count?
Implement a bounded retry helper
Practice prompt: Wrap a fallible operation with retries while keeping the API predictable and the total work bounded.
Solution approach:
- Specify retryable failures, maximum attempts, per-attempt timeout and an overall deadline. Attempt count and retry count are different; name the configuration unambiguously.
- Use bounded backoff and jitter where many callers could retry together. Preserve cancellation and propagate the final error with useful context.
- Inject time and randomness for tests. Do not automatically retry a non-idempotent side effect unless the operation has a stable deduplication or recovery contract.
Follow-up: How would you honor server-provided retry guidance without exceeding the caller’s deadline?
Build a rate limiter
Practice prompt: Protect an API with a stated request-rate policy and support concurrent callers.
Solution approach:
- Choose a policy before a data structure: fixed window, sliding window or token bucket each allows different bursts. Define the tenant key, clock and what counts as one request.
- Update the decision state atomically. A distributed deployment needs a shared authority or an explicit approximation; independent per-node counters do not enforce a strict global limit.
- Test boundary timestamps, bursts, concurrent requests and store failure. Specify rejection status, retry guidance and whether the limiter fails open or closed for this workload.
Follow-up: How would you combine a per-tenant limit with a global downstream capacity limit?
Apply non-conflicting text annotations
Practice prompt: Apply labeled spans to text while defining how overlapping ranges are represented.
Solution approach:
- Specify whether indices refer to bytes, code points or another unit, and whether end positions are exclusive. Preserve the unmodified text as the coordinate system for all ranges.
- Sort boundary events and construct output in one pass instead of inserting tags repeatedly into a shifting string. Overlapping spans may require splitting or a precedence rule to avoid invalid nesting.
- Test identical boundaries, nested ranges, crossing ranges and labels requiring escaping. State the chosen policy before solving ambiguous overlap cases.
Follow-up: How would you preserve the original source offsets after producing the annotated representation?
Explain a complex project
Practice prompt: Walk through a project you owned, including the difficult decisions and your individual contribution.
Solution approach:
- Begin with the user problem and constraints, then draw the smallest useful architecture. Identify what you implemented, what others owned and which decisions you influenced.
- Explain one rejected option and the evidence behind the choice. Describe a failure case and how the system or team recovered.
- Give a verifiable result without inventing metrics. End with what you would change today and why new information would justify that change.
Follow-up: Which decision would you revisit first if the workload grew tenfold?
Deliver under a tight deadline
Practice prompt: Explain how you prioritized a real project when time or staffing was constrained.
Solution approach:
- State the deadline, the user consequence and the work that was essential. Distinguish a fixed external constraint from an assumption the team could negotiate.
- Explain what you deferred, which quality checks you kept and how stakeholders accepted the tradeoff. A smaller safe delivery can be more useful than an untested full scope.
- Give the actual result and one lesson. If the deadline was missed, describe when you raised the risk and how the team recovered.
Follow-up: What would you change if the deadline stayed fixed but a key dependency became unavailable?
Design walkthrough: document traceability and bounded inference
Use this exercise to connect the selected topics to a plausible application in AI tools for legal and professional work. The diagram is a preparation model with deliberately simplified boundaries. It is not a claim about the company's deployed systems.
Scenario: A document result being attributed to the wrong source passage. Explain how the system discovers the discrepancy, what remains authoritative and what a user can do while recovery is in progress.
Establish the contract
Start at authorize document access. Define the input identity, the caller's permissions and the result that counts as acceptance. Use one normal request and one invalid request to test whether your description is precise. If the operation can be repeated, decide whether a retry means another attempt at the same work or an intentionally new operation.
Then explain track text boundaries. Identify what is checked before state changes and what may still fail afterward. Avoid a success response that implies more than the system has actually completed. An accepted request, a durable record, a delivered message and a refreshed screen can be four different milestones.
Put ownership where the invariant lives
At run bounded processing, name the record or state transition that must remain correct when two callers race. Choose a transaction, conditional update or single owner for that invariant. Describe the losing caller's result as carefully as the winning caller's result. A lock or queue is useful only if it protects the right boundary.
Keep derived displays and reports separate from authoritative state. Write down which version a displayed result represents and how that version is invalidated or refreshed. If a view may lag, define how the user recognizes that it is pending or stale. Do not hide an uncertain outcome behind a generic error message that encourages uncontrolled retries.
Make the failure observable
Now exercise attach source references with a slow or unavailable dependency. Trace the identifier through the request, durable record, asynchronous work and final view. For the scenario above, show one concrete discrepancy between expected and observed state and the evidence that distinguishes an incomplete operation from a completed operation whose response was lost.
Finish with verify output against input. A recovery procedure should explain who can perform it, how repeated execution is made safe and what evidence proves completion. Bound retries and surface work that cannot progress automatically. Keep the original failure visible long enough to investigate rather than deleting the evidence as part of a replay.
Test the design before adding more components
Run four variations: a duplicate request, an out-of-order observation, a dependency timeout and an unauthorized caller. For each, record the expected durable state and the user-visible result. If a variation does not apply to your chosen operation, explain why instead of adding a mechanism by habit.
Only then discuss scaling. Identify the first likely bottleneck using the work performed per request, the size of retained state and the slowest dependency. More replicas can amplify a shared database or queue bottleneck. Explain what you would measure before choosing sharding, caching or another independently deployed service.
Explain your reasoning in the interview
Make the first answer small and correct
Begin with the contract and a simple approach. Explain its cost and limitations, then improve the part that conflicts with a stated constraint. If you propose an optimization, preserve a test that demonstrates the original behavior. In a design discussion, a small system with a clear failure contract is easier to evaluate than a large diagram with unnamed responsibilities.
Handle a changed requirement explicitly
When the interviewer adds concurrency, a larger dataset or a failing dependency, pause and name the assumption that changed. Describe what remains correct and which boundary needs revision. Do not restart the entire answer unless the new requirement invalidates the original model. This makes adaptation visible and gives the interviewer a chance to correct your interpretation early.
Bring a project story with evidence
Prepare an example relevant to document traceability and bounded inference. Explain the constraint, your personal contribution, an alternative you considered and the outcome you verified. If you lack professional experience in this domain, use a course or personal project honestly and describe what extra controls production work would need. Never invent traffic numbers, savings or responsibility to make the story sound more senior.
A two-week preparation plan
This is a suggested schedule, not Harvey's interview timeline. Move effort toward the confirmed assessment and the topics where your first attempt exposed a gap.
| Session | Concrete output |
|---|---|
| Days 1–2 | A role brief and an attempted answer to minimum concurrent machines. |
| Days 3–4 | A tested answer to implement a bounded retry helper, including one failure or boundary case. |
| Days 5–6 | Rehearse build a rate limiter and explain a changed requirement. |
| Days 7–8 | Complete apply non-conflicting text annotations and compare your reasoning with its checklist. |
| Days 9–10 | Work through explain a complex project and deliver under a tight deadline. |
| Days 11–12 | Annotate the design diagram with ownership, failure and recovery. |
| Days 13–14 | Run a mock, repair the weakest answer and prepare questions for the team. |
After each session, record what you could not explain without looking at the answer. Turn that uncertainty into a small test, diagram or documented example. Repeating a question is useful when the second attempt demonstrates a specific improvement, such as a clearer invariant or a previously missed edge case.
Questions to ask the team
Ask which user workflow needs the most attention, how the team knows a change is working and where engineers spend time diagnosing failures. For Harvey, use the discussion of document traceability and bounded inference to make the questions concrete: which system owns the truth, which views may lag and who handles discrepancies between them?
Also ask how code reviews, production support and onboarding work for this specific role. The answers help you assess the work and prepare relevant examples without assuming that every team at one company has the same stack or responsibilities.
Frequently asked questions
Are these confirmed Harvey interview questions?
The six topics are selected from a third-party company guide; the problem clarifications, solution approaches, diagrams and follow-ups are PracHub preparation material. The third-party listing is not independent confirmation that this team asks these questions. Use current recruiter instructions for the actual format.
Do I need to use the language shown in a reference?
Use the language required by the assessment, or your strongest suitable language when there is a choice. Reference documentation helps verify behavior; it does not prove the employer requires that language. Be ready to explain your data structures and test cases without relying on memorized syntax.
What if I have only a weekend?
Complete the first two selected questions, trace the design failure above and prepare one honest project story. Prefer a few answers you can defend over a wide list of topics you cannot explain. For more exercises, use the PracHub Software Engineer question bank.
Sources and further reading
- Harvey: company background — context on AI tools for legal and professional work; use the actual vacancy to establish role requirements.
- Dataford: Harvey Software Engineer guide — source of the selected practice topics, with PracHub-authored explanations and follow-ups. Its company-question attribution has not been independently confirmed.
- Python data structures — Review sequences, dictionaries, sets and their behavior when implementing the coding exercises.
- MDN HTTP overview — Check HTTP request, response and connection semantics when defining an API contract.