Software Engineers at Overjet build the cutting-edge artificial intelligence platform that is transforming the dental industry. By analyzing dental radiographs and clinical data, Overjet's software helps dentists deliver more accurate, data-driven diagnoses and assists insurance companies in streamlining claims processing. As a engineer in this space, you will work at the intersection of computer vision, clinical workflows, and cloud-scale software. Your work will directly influence patient outcomes by ensuring AI insights are delivered fast, reliably, and seamlessly into clinical practices. You will tackle complex problems including processing high-resolution medical imaging, integrating with legacy dental practice management systems, and designing highly interactive visualization tools for dental practitioners. This role is critical to scaling the company's core products and maintaining its position as a leader in dental AI. The engineering culture at Overjet is highly collaborative, fast-paced, and product-focused. You will work alongside smart, passionate professionals who enjoy solving complex technical challenges. For a, this environment offers the unique opportunity to drive significant business impact while working on a product that genuinely improves people's health and well-being. Software Engineer
Recruiter Screening Call
reportedInitial call led by a recruiter to explain company culture and role expectations.
What to demonstrate
- Initial call led by a recruiter to explain company culture and role expectations
- Depth in Software Engineering Problem Solving
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 and Architectural Rounds
reportedSeries of technical assessments focusing on deep technical execution.
What to demonstrate
- Series of technical assessments focusing on deep technical execution
- Depth in Software Engineering Problem Solving
How to prepare
- Answer aloud and timed: How do you optimize database queries and manage state in a highly interactive web application?
- Answer aloud and timed: Explain how you handle data consistency and synchronization across distributed services.
Discussions with Engineering Leadership
reportedFinal discussions with engineering directors and managers to evaluate behavioral alignment.
What to demonstrate
- Final discussions with engineering directors and managers to evaluate behavioral alignment
- Depth in Software Engineering Problem Solving
How to prepare
- Answer aloud and timed: Design a system that can ingest, process, and store thousands of high-resolution dental scans concurrently.
- Answer aloud and timed: Develop a technical solution to a real-time data visualization challenge and write the corresponding code.
PracHub editorial advice for the preparation topics above.
Be Prepared to Write Real Code
Do not expect to just draw boxes and arrows during the design phase. Brush up on your coding fundamentals and be ready to implement your architectural ideas in actual code.
During your design exercise, treat the interviewer as a collaborator
Talk through your decisions, ask clarifying questions, and be receptive to feedback as you write code.
Be Ready for Deep Dives into Past Projects
Interviewers will ask about the complexity of your past engineering work. Be prepared to detail the exact technical challenges you faced, your problem-solving approach, and the impact of your solutions.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Implement a algorithm to detect overlapping regions or annotations on a 2D grid.
Implement a algorithm to detect overlapping regions or annotations on a 2D grid.
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?
Find overlapping job attempts and peak concurrency from lease records
A day of job_run history yields about 50,000,000 attempt records: (job_run_id, job_type, attempt, started_at, finished_at which is NULL when the worker died, lease_expires_at). Leases expire on a clock, so a job that outran its lease ran twice. Produce (a) every job_run_id whose attempts overlapped in wall-clock time and (b) the peak number of simultaneously running attempts per job_type with the minute it occurred. Target O(n log n). State how you treat a NULL finished_at and what clock skew does to your answer.
Approach
- Define the interval before sorting anything: an attempt occupies [started_at, COALESCE(finished_at, lease_expires_at)). finished_at is observed and lease_expires_at is only a promise, so every attempt without a finish contributes an estimate and the whole result is a lower bound on overlap rather than an exact count.
- For peak concurrency, sweep: emit 2n endpoints, sort by (timestamp, kind) with ends ordered before starts at equal timestamps, then walk the sequence maintaining a counter per job_type and record each type's maximum with its timestamp. O(n log n) dominated by the sort, O(n) space, or O(1) extra if the sort is external and the walk streams.
- For overlap detection, do not compare attempts pairwise. A single global sort by (job_run_id, started_at) gives both the grouping and the order; within a group, keep the maximum end seen so far and report an overlap exactly when the next start is less than that running maximum, which is one linear pass after the sort.
- Half-open intervals matter and are easy to get wrong: with closed intervals an attempt ending at the same millisecond another begins reads as concurrency two, and across 50,000,000 records that artefact swamps the real signal.
Follow-up
- A handler is not idempotent and you have found 400 overlapping jobs. Which of them actually caused damage, and what would you query to find out?
- Peak concurrency for one job_type is 4 against a configured cap of 4. Is the cap working, or is the data hiding attempts that never started?
Merge partitioned event streams into one ordered feed with bounded lateness
The read-model service consumes 64 log partitions carrying about 4,000 events per second in total. Each partition is ordered within itself, but partitions drift by up to 30 seconds, and the activity feed must present a tenant's events in occurred_at order. Produce the merge. State its complexity, the buffer it requires in events and in bytes, what happens when one partition is idle, and what you do with an event that arrives after you have already emitted its position. Payloads average 1 KB.
Approach
- Merge with a min-heap over the 64 partition heads keyed on (occurred_at, event_id): O(log P) per event and O(n log P) overall. The tie-break on event_id is what makes the output deterministic when two partitions carry the same millisecond, which matters because the feed is paginated and a non-deterministic order reorders pages under the reader.
- Emitting the heap head is only correct once every partition has produced everything up to that timestamp, so the emit condition is a watermark: the minimum across partitions of the highest occurred_at seen, less the allowed lateness. Events are held until the watermark passes them, which is what turns individually ordered streams into a jointly ordered one.
- Size the buffer from the lateness rather than guessing: 4,000 events per second times 30 seconds is 120,000 buffered events, and at 1 KB each about 120 MB of heap. That number is the real price of the ordering guarantee and belongs in front of whoever asked for it.
- Handle the idle partition explicitly, because it fails the feed rather than corrupting it: a partition with no traffic never advances its own maximum, so the watermark freezes and output stops entirely. Either every partition emits a periodic idle marker carrying the broker's current time, or the watermark falls back to wall clock for a partition silent beyond a threshold.
Follow-up
- The lateness budget is raised to five minutes. What is the new buffer, and what besides memory changes?
- The consumer restarts. Where does it resume from, and what does the feed look like for the first 30 seconds?
Hold a per-tenant active cap against concurrent creates
A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.
Approach
- Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
- Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
- Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
- State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.
Follow-up
- A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
- The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?
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?
Describe the most technically complex software engineering problem you have tackled. What made it complex, and
Describe the most technically complex software engineering problem you have tackled. What made it complex, and how did you solve it?
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 optimize database queries and manage state in a highly interactive web application?
How do you optimize database queries and manage state in a highly interactive web application?
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 handle data consistency and synchronization across distributed services.
Explain how you handle data consistency and synchronization across distributed services.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Design a system that can ingest, process, and store thousands of high-resolution dental scans concurrently.
Design a system that can ingest, process, and store thousands of high-resolution dental scans concurrently.
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?
Develop a technical solution to a real-time data visualization challenge and write the corresponding code.
Develop a technical solution to a real-time data visualization challenge and write the corresponding code.
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 architect an API that integrates a machine learning model pipeline with a frontend clinical dash
How would you architect an API that integrates a machine learning model pipeline with a frontend clinical dashboard?
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?
Exports duplicate a row range about once a week
Roughly once a week an export writes a file containing a duplicated range of rows. The affected job_run rows show attempt = 1, status = succeeded, one started_at, and a lease_owner naming a different host from the one whose logs show the job starting. Leases last 30 seconds and are heartbeated every 10 from inside the handler; lease_expires_at is computed on the worker and compared against the database's now(). Find the mechanism, and give a fix that holds even if you cannot fix the clocks.
Approach
- Start from the fact that eliminates the obvious answer. attempt = 1 means no retry was recorded, so this is not a re-run after failure; two workers ran the same row concurrently and the takeover path never touched the counter. lease_owner naming a host other than the one that started the job is the same statement from the other side.
- Enumerate the mechanisms that cause a premature takeover, then find the signal that separates them. Either the lease genuinely expired because the heartbeat did not fire, which is what happens when the heartbeat runs on the handler's own thread and the handler makes a long blocking call, or it only appeared expired because two clocks disagree, since lease_expires_at is written from the worker's clock and evaluated against the database's. The discriminator is the distribution: incidents clustered on the longest exports indict the heartbeat, incidents clustered on one host indict skew. Measure both, and measure each host's offset against the database directly.
- Read the reclaim query precisely. In PostgreSQL now() is transaction start time, not statement time, so a reclaimer holding a long transaction compares against an older timestamp than expected; clock_timestamp() is the statement-time function. This is worth ruling in or out before you redesign anything, because it changes which rows look expired.
- Remove the second clock rather than trying to synchronise it. Issue and extend the lease in the database, with lease_expires_at = now() + interval '30 seconds' in both the claim and the heartbeat, so exactly one clock is ever compared and worker skew stops mattering to this predicate.
Follow-up
- The displaced worker has already streamed half the file to object storage. What makes that side effect safe to repeat?
- You now count takeovers. What alert fires on that counter, and at what threshold?
Built from the rounds and topics Overjet candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Overjet loop
- Write out the reported sequence: Recruiter Screening Call, Technical and Architectural Rounds, Discussions with Engineering Leadership.
- 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 Software Engineering Problem Solving
- Spend the session on Software Engineering Problem Solving, which Overjet candidates report being tested on.
- Write one worked example in Software Engineering Problem Solving and time yourself on it.
Deliverable: One timed worked example in Software Engineering Problem Solving.
03Work System Design (Technical Design Exercise)
- Spend the session on System Design (Technical Design Exercise), which Overjet candidates report being tested on.
- Write one worked example in System Design (Technical Design Exercise) and time yourself on it.
Deliverable: One timed worked example in System Design (Technical Design Exercise).
04Work Technical Coding Ability
- Spend the session on Technical Coding Ability, which Overjet candidates report being tested on.
- Write one worked example in Technical Coding Ability and time yourself on it.
Deliverable: One timed worked example in Technical Coding Ability.
05Answer out loud: Technical & Domain Knowledge
- Answer aloud, timed: Walk me through your experience with our tech stack and how you have applied it in your past roles.
- Answer aloud, timed: Describe the most technically complex software engineering problem you have tackled. What made it complex, and how did you solve it?
Deliverable: Spoken answers to 2 reported Technical & Domain Knowledge question(s), under time.
06Answer out loud: System Design & Coding
- Answer aloud, timed: Design a system that can ingest, process, and store thousands of high-resolution dental scans concurrently.
- Answer aloud, timed: Develop a technical solution to a real-time data visualization challenge and write the corresponding code.
Deliverable: Spoken answers to 2 reported System Design & Coding question(s), under time.
07Answer out loud: Behavioral & Collaboration
- Answer aloud, timed: Tell me about a time you had a significant design disagreement with a teammate or lead. How did you handle it and what was the outcome?
- Answer aloud, timed: Describe a project you managed from technical design to deployment. How did you handle competing priorities and shifting timelines?
Deliverable: Spoken answers to 2 reported Behavioral & Collaboration question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Walk me through your experience with our tech stack and how you have applied it in your past roles.
Walk me through your experience with our tech stack and how you have applied it in your past roles.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Tell me about a time you had a significant design disagreement with a teammate or lead. How did you handle it
Tell me about a time you had a significant design disagreement with a teammate or lead. How did you handle it and what was the outcome?
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 project you managed from technical design to deployment. How did you handle competing priorities an
Describe a project you managed from technical design to deployment. How did you handle competing priorities and shifting timelines?
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 incorporate continuous feedback into your development workflow? Give an example of how feedback imp
How do you incorporate continuous feedback into your development workflow? Give an example of how feedback improved your work.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Tell me about a time you had to work with a product manager to refine requirements for an ambiguous feature.
Tell me about a time you had to work with a product manager to refine requirements for an ambiguous feature.
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
Walk me through your experience with our tech stack and how you have applied it in your past roles.
- 02
Tell me about a time you had a significant design disagreement with a teammate or lead. How did you handle it and what was the outcome?
- 03
Describe a project you managed from technical design to deployment. How did you handle competing priorities and shifting timelines?
- 04
How do you incorporate continuous feedback into your development workflow? Give an example of how feedback improved your work.
How difficult is the Software Engineer interview process at Overjet?
The process is generally described as average in difficulty but thorough. It focuses on practical coding, system design, and behavioral alignment rather than abstract brainteasers or high-pressure trivia.
Overjet Software Engineer candidate reports ↗What is the typical timeline for the interview process?
The process typically takes between 2 to 3 weeks from the initial recruiter screen to the final round. However, timeline variations can occur depending on team availability and scheduling.
Overjet Software Engineer candidate reports ↗How does Overjet evaluate culture fit?
Overjet values transparency, collaboration, and a strong product-driven mindset. Leaders look for candidates who handle feedback well, communicate their ideas clearly, and show genuine excitement for solving complex health-tech problems.
Overjet Software Engineer candidate reports ↗Will I be required to write code during the system design round?
Yes, unlike traditional system design interviews that are purely theoretical, Overjet's design exercise often involves developing a solution to a technical challenge and writing real code alongside a senior engineer.
Overjet Software Engineer candidate reports ↗What topics does Overjet test in interviews?
Overjet interviews most often cover Stakeholder Management, Time Management in Interviews, Software Engineering Problem Solving, Problem Solving, and Domain Knowledge (Dental / Healthcare). The exact emphasis depends on the specific role you apply for.
Overjet 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.
- 01Overjet 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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