As a Software Engineer at Oho Group, you are joining a high-growth environment characterized by technical ambition and a focus on solving complex, real-world challenges. Whether you are working on cutting-edge security technology or scaling systems for Applied AI, the role is designed for engineers who thrive on building production-grade software from the ground up. You will contribute to a culture shaped by talent from world-class organizations, working alongside peers who prioritize engineering excellence and high-velocity delivery. This position is critical to the company’s mission, as you will be responsible for designing and delivering systems that must operate reliably at scale. You are expected to take ownership of your work, moving beyond incremental tasks to tackle fundamental engineering problems. By joining Oho Group, you place yourself at the intersection of sophisticated technical challenges and rapid business growth, offering a unique opportunity to influence the trajectory of a company backed by leading global investors.
Application Review
reportedInitial review of candidate applications to assess qualifications and fit.
What to demonstrate
- Initial review of candidate applications to assess qualifications and fit
- Depth in Software Engineering Fundamentals
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 Assessment
reportedCandidates undergo technical evaluations to gauge their skills and knowledge.
What to demonstrate
- Candidates undergo technical evaluations to gauge their skills and knowledge
- Depth in Software Engineering Fundamentals
How to prepare
- Answer aloud and timed: What are the trade-offs when choosing between different data structures for high-performance applications?
- Answer aloud and timed: How do you approach testing and debugging in a distributed systems environment?
Behavioral Interview
reportedAssessment of cultural fit and alignment with company values through behavioral questions.
What to demonstrate
- Assessment of cultural fit and alignment with company values through behavioral questions
- Depth in Software Engineering Fundamentals
How to prepare
- Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
- Re-read the description of the behavioral interview above and write down what you would ask to confirm before it.
Deep-Dive Technical Rounds
reportedIn-depth technical discussions with engineering team members to evaluate expertise.
What to demonstrate
- In-depth technical discussions with engineering team members to evaluate expertise
- Depth in Software Engineering Fundamentals
How to prepare
- Answer aloud and timed: Discuss your experience with distributed systems and how you manage state across multiple services.
- Answer aloud and timed: If you were tasked with putting an AI agent into production, what are the primary architectural challenges you would anticipate?
Final Communication
reportedClear communication regarding the candidate's progress and next steps in the process.
What to demonstrate
- Clear communication regarding the candidate's progress and next steps in the process
- Depth in Software Engineering Fundamentals
How to prepare
- Answer aloud and timed: How do you balance the need for rapid feature delivery with the necessity of long-term system stability?
- Answer aloud and timed: What strategies do you employ to monitor and optimize the performance of production-grade systems?
PracHub editorial advice for the preparation topics above.
Own your narrative
Be prepared to talk about your projects with deep technical detail; interviewers at Oho Group value candidates who can explain the reasoning behind their architectural choices.
Focus on production
Regardless of whether you are interviewed for security or AI, always frame your answers around how your code performs in a real-world, production environment.
Be proactive
In your behavioral answers, highlight instances where you identified a problem and took the initiative to solve it without waiting for specific instructions.
Know the stack
Be very comfortable with the languages mentioned in the job description; you will likely be expected to write code or debug issues in one of these during the technical rounds.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Explain the key differences in managing memory and concurrency in your preferred programming language.
Explain the key differences in managing memory and concurrency in your preferred programming language.
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 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?
Track a rolling failure rate per destination for circuit decisions
The egress service delivers about 1,500 webhooks per second across roughly 40,000 destinations, each call bounded by a 10 second timeout. Maintain, per destination, the failure rate over the trailing 60 seconds so a caller can ask before dispatch whether the circuit should open. Attempts arrive as (destination_id, finished_at_ms, outcome). Requirement: amortised O(1) per attempt, with total memory bounded by the destination count rather than by traffic. Give the structure, its exact memory, and the rule that stops a destination with three attempts from opening a circuit.
Approach
- Name the exact-deque version and then reject it as the default. Holding timestamps and advancing a tail pointer past anything older than now minus 60 seconds is a correct two-pointer window at amortised O(1) per attempt, but its memory tracks in-window traffic, so one destination in a retry storm holds hundreds of thousands of entries while thousands of quiet destinations hold none.
- Use a ring of 60 one-second buckets per destination, each bucket a pair of counters for attempts and failures. On an attempt, advance the ring by the elapsed whole seconds, zeroing at most min(elapsed, 60) buckets, then increment the head. That is amortised O(1) with a fixed footprint per destination.
- State the footprint: 60 buckets times two 4-byte counters is 480 bytes of payload per destination, so 40,000 destinations is roughly 20 to 25 MB with per-entry overhead, bounded by the catalogue rather than by the rate. The cost is granularity, since the oldest bucket ages out in whole seconds, which is far tighter than the decision needs.
- Require a minimum sample before the circuit may open. A destination with three attempts and three failures reads as 100 percent and is not evidence; a floor of roughly 20 attempts in the window makes the ratio meaningful, and below that floor use a run of consecutive failures as the trigger instead.
Follow-up
- The fleet is 30 instances and each sees roughly a thirtieth of a destination's traffic. Where does the rate actually live, and what does a per-instance answer get wrong?
- A destination answers in 9.5 seconds and succeeds. It is not failing but it is consuming your per-destination concurrency. What signal should open the circuit here?
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?
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?
How do you ensure code quality and maintainability in a fast-moving, high-growth environment?
How do you ensure code quality and maintainability in a fast-moving, high-growth environment?
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?
Can you walk through a complex technical problem you solved using C++, Java, Rust, or Python?
Can you walk through a complex technical problem you solved using C++, Java, Rust, or Python?
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?
What are the trade-offs when choosing between different data structures for high-performance applications?
What are the trade-offs when choosing between different data structures for high-performance applications?
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 system to handle high-concurrency requests while maintaining strict security standards?
How would you design a system to handle high-concurrency requests while maintaining strict security standards?
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?
If you were tasked with putting an AI agent into production, what are the primary architectural challenges you
If you were tasked with putting an AI agent into production, what are the primary architectural challenges you would anticipate?
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 balance the need for rapid feature delivery with the necessity of long-term system stability?
How do you balance the need for rapid feature delivery with the necessity of long-term system stability?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
What strategies do you employ to monitor and optimize the performance of production-grade systems?
What strategies do you employ to monitor and optimize the performance of production-grade systems?
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 approach testing and debugging in a distributed systems environment?
How do you approach testing and debugging in a distributed systems environment?
Approach
- Establish what changed and when, before forming any theory.
- Pick a bisection that eliminates candidates whichever way it turns out.
- Check the instrumentation before believing the symptom.
- Separate the trigger from the cause; the deploy is rarely the bug.
Follow-up
- What would you look at first, and what would it rule out?
- How would you tell a cause from a coincidence here?
Built from the rounds and topics Oho Group candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Oho Group loop
- Write out the reported sequence: Application Review, Technical Assessment, Behavioral Interview, Deep-Dive Technical Rounds, Final Communication.
- 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 5 reported rounds, with the weakest marked.
02Work Software Engineering Fundamentals
- Spend the session on Software Engineering Fundamentals, which Oho Group candidates report being tested on.
- Write one worked example in Software Engineering Fundamentals and time yourself on it.
Deliverable: One timed worked example in Software Engineering Fundamentals.
03Work Backend Engineering
- Spend the session on Backend Engineering, which Oho Group candidates report being tested on.
- Write one worked example in Backend Engineering and time yourself on it.
Deliverable: One timed worked example in Backend Engineering.
04Work Programming in Python
- Spend the session on Programming in Python, which Oho Group candidates report being tested on.
- Write one worked example in Programming in Python and time yourself on it.
Deliverable: One timed worked example in Programming in Python.
05Answer out loud: Technical Fundamentals and Proficiency
- Answer aloud, timed: How do you ensure code quality and maintainability in a fast-moving, high-growth environment?
- Answer aloud, timed: Can you walk through a complex technical problem you solved using C++, Java, Rust, or Python?
Deliverable: Spoken answers to 2 reported Technical Fundamentals and Proficiency question(s), under time.
06Answer out loud: System Design and Architecture
- Answer aloud, timed: How would you design a system to handle high-concurrency requests while maintaining strict security standards?
- Answer aloud, timed: Discuss your experience with distributed systems and how you manage state across multiple services.
Deliverable: Spoken answers to 2 reported System Design and Architecture question(s), under time.
07Answer out loud: Behavioral and Leadership
- Answer aloud, timed: Describe a time you had to influence a team’s technical direction. How did you build consensus?
- Answer aloud, timed: How do you handle disagreements regarding technical architecture or coding standards?
Deliverable: Spoken answers to 2 reported Behavioral and Leadership 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.
Discuss your experience with distributed systems and how you manage state across multiple services.
Discuss your experience with distributed systems and how you manage state across multiple services.
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 you had to influence a team’s technical direction. How did you build consensus?
Describe a time you had to influence a team’s technical direction. How did you build consensus?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
How do you handle disagreements regarding technical architecture or coding standards?
How do you handle disagreements regarding technical architecture or coding standards?
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?
What is your approach to mentorship and elevating the engineering standards of those around you?
What is your approach to mentorship and elevating the engineering standards of those around you?
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 us about a project where you took full ownership from design to deployment; what were the biggest hurdles
Tell us about a project where you took full ownership from design to deployment; what were the biggest hurdles?
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 stay proactive and adapt when project requirements change suddenly?
How do you stay proactive and adapt when project requirements change suddenly?
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
Discuss your experience with distributed systems and how you manage state across multiple services.
- 02
Describe a time you had to influence a team’s technical direction. How did you build consensus?
- 03
How do you handle disagreements regarding technical architecture or coding standards?
- 04
What is your approach to mentorship and elevating the engineering standards of those around you?
How difficult are the interviews at Oho Group?
The interviews are considered highly rigorous and challenging, reflecting the company’s focus on high-growth, technically complex work. You should expect in-depth technical grilling, but the process is structured to be transparent and rewarding for those who prepare well.
Oho Group Software Engineer candidate reports ↗What is the typical timeline for the interview process?
While timelines can vary based on the specific team and role, the process is generally designed to move at a pace that matches the company's rapid growth. Most candidates progress through the stages within a few weeks, provided they are responsive and prepared.
Oho Group Software Engineer candidate reports ↗Is there a specific focus on cultural fit?
Yes, Oho Group prioritizes engineers who are proactive, collaborative, and comfortable with ambiguity. They look for individuals who want to take ownership of their work and contribute to a high-velocity engineering culture.
Oho Group Software Engineer candidate reports ↗What should I know about visa requirements?
Ensure you have a clear understanding of your visa status before applying. The company requires candidates to have a permanent, pre-settlement, or indefinite right to remain in the UK to be considered for these roles.
Oho Group Software Engineer candidate reports ↗What topics does Oho Group test in interviews?
Oho Group interviews most often cover Software Engineering Fundamentals, Backend Engineering, Interview Process Management, Programming in Python, and AI Engineering (Applied AI). The exact emphasis depends on the specific role you apply for.
Oho Group 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.
- 01Oho Group 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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