As a Software Engineer at Lhh, you occupy a dynamic and highly impactful role within a global leader in talent solutions, career transition, and leadership development. Because LHH operates both as an enterprise product creator and a strategic talent consultancy, software engineering here carries a unique dual responsibility. You may find yourself building and scaling the proprietary digital platforms that power global career transition and recruitment, or you may be deployed as a highly skilled technical consultant to drive critical engineering initiatives directly for LHH's diverse portfolio of enterprise clients. Your work directly impacts how millions of professionals navigate their careers and how global organizations optimize their workforces. This requires not only high-caliber technical execution but also a deep understanding of user experience, platform scalability, and data security. Whether optimizing internal backend services or developing client-facing applications, you will solve complex architectural challenges that directly influence the company’s digital transformation journey. This role is ideal for engineers who thrive on variety, value direct business impact, and possess the adaptability to navigate different technical ecosystems. The engineering culture at LHH values collaboration, problem-solving agility, and a strong sense of ownership over the end-to-end delivery of software solutions.
Recruiter Screening Call
reportedInitial call focusing on your background, career aspirations, and salary expectations.
What to demonstrate
- Initial call focusing on your background, career aspirations, and salary expectations
- Depth in Recruiter/Interview Process Management
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.
Exploratory and Behavioral Interview
reportedIn-depth interview assessing your behavioral alignment and exploratory discussions.
What to demonstrate
- In-depth interview assessing your behavioral alignment and exploratory discussions
- Depth in Recruiter/Interview Process Management
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 exploratory and behavioral interview above and write down what you would ask to confirm before it.
Technical Assessment
reportedEvaluation of your technical capabilities, possibly including a project alignment discussion.
What to demonstrate
- Evaluation of your technical capabilities, possibly including a project alignment discussion
- Depth in Recruiter/Interview Process Management
How to prepare
- Answer aloud and timed: How do you approach tracking project requirements, technical documentation, and purchase orders or submittals in a fast-paced project?
- Answer aloud and timed: Describe a time when you identified a potential technical delay in a project. What steps did you take to mitigate the risk and keep the timeline on track?
Client Interview
reportedInterview with the client company to ensure a good match for the project's operational context.
What to demonstrate
- Interview with the client company to ensure a good match for the project's operational context
- Depth in Recruiter/Interview Process Management
How to prepare
- Answer aloud and timed: How do you balance the need for high-quality, clean code with the pressure of strict project deadlines?
- Answer aloud and timed: Explain your approach to evaluating third-party tools or bids when deciding on a technical solution for a project.
PracHub editorial advice for the preparation topics above.
Clarify Project Context Early
Always ask whether the role is focused on internal product development or external client consulting, as this will help you tailor your answers to highlight either product-scaling or client-management expertise.
Quantify Your Impact
When discussing your past projects, use specific metrics to demonstrate your contribution. Mention how your work improved system performance, reduced development time, or prevented potential project delays.
Assuming the input fits in memory
Ask how large the input is in bytes before committing to an in-memory algorithm; beyond that point the options are a single streaming pass, an external sort with bounded buffers, or a sketch that trades exactness for constant memory. An algorithm that assumes random access to the whole input is a different algorithm from one that sees each element once.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Canonicalise a request body into a stable idempotency fingerprint
idempotency_key.request_fingerprint is a SHA-256 over the method, path and canonicalised body, and a retry whose fingerprint differs must be rejected with 422 rather than served the stored response. Write the canonicaliser. Bodies are JSON up to 256 KB nested at most 32 levels; clients vary key order, whitespace and unicode escaping, and some send 64-bit ids as JSON numbers. Produce a deterministic byte string such that semantically identical bodies match and any semantic difference does not. State your complexity and name two normalisations you refuse to perform.
Approach
- Parse once into a tree, then re-serialise under fixed rules: object keys sorted, array order preserved, one escaping convention, no insignificant whitespace. Parsing is O(n) and sorting keys is O(k log k) per object, so O(n log n) overall with O(depth) stack, and the 32-level cap is enforced during parsing because hostile nesting is how a canonicaliser becomes a stack overflow.
- Sort keys by their UTF-8 bytes and say why the obvious implementation is wrong in some runtimes: a default string comparison that orders by UTF-16 code units places surrogate pairs, meaning code points from U+10000 up, below U+E000 to U+FFFF, which is not UTF-8 byte order, so two services written in different languages disagree on the same document.
- Do not re-encode numbers through a double. IEEE-754 binary64 represents integers exactly only up to 2^53, so normalising a 19-digit id through a float changes it, and 1 against 1.0 cannot be reconciled without deciding whether they are the same value. Preserve the literal token, and require ids as strings at the API boundary if you want them comparable.
- Reject duplicate keys rather than picking one. JSON permits them and parsers disagree, most keeping the last, so any choice you make ties the fingerprint to a parser detail that the code handling the request does not necessarily share.
Follow-up
- A client sends the same logical request with an extra field your API ignores. Same key, different fingerprint, so you return 422. Is that the right answer?
- Where does the fingerprint get computed relative to request decompression and the body-size limit?
Collapse a redelivered event batch into per-aggregate high-water marks
You drain a batch of up to 5,000,000 events, each (aggregate_id BIGINT, aggregate_version INT, event_type, payload). The log guarantees order within one aggregate only; the batch merges 64 partitions, and a relay failover has redelivered a range, so an older version for an aggregate can appear after a newer one. Given a map of last_applied_version per aggregate, produce the events worth applying, at most one per (aggregate_id, version), plus the count discarded. Target O(n) time. State the memory for 2,000,000 distinct aggregates and what you do when it does not fit.
Approach
- One pass, one hash map from aggregate_id to the highest version kept, and a discard counter. An event whose version is at or below last_applied_version for its aggregate is dropped without further work, which is the whole reason the event carries its version rather than a delta. O(n) expected time, O(d) space in distinct aggregates.
- Keep the maximum, never the last occurrence. The redelivered range means the final appearance of an aggregate in the batch can be an older version than one seen earlier in the same batch, so last-wins applies stale state over newer state and the projection regresses with no error anywhere.
- Cost the memory instead of calling it large: an 8-byte key plus a 4-byte version is 12 bytes of payload, and an open-addressed table held at a 0.7 load factor costs roughly 17 bytes per entry before per-slot metadata, so 2,000,000 aggregates is tens of megabytes in a native layout and several times that in a runtime that boxes both key and value.
- If the distinct set exceeds memory, partition on hash(aggregate_id) mod P and reduce each partition independently. Every event for one aggregate hashes to the same partition, so the per-partition result is exact and the merge is concatenation rather than a second reduction.
Follow-up
- The payload is a patch rather than a snapshot, so applying only the highest version loses the intermediate changes. What changes in your reduction?
- How do you detect that version 7 arrived while version 6 was never delivered, and what should the consumer do about the gap?
Identify the heaviest tenants in a five-minute window under memory pressure
The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.
Approach
- Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
- Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
- State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
- Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.
Follow-up
- The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
- Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?
What motivates you to join LHH as a Software Engineer, and how do you see yourself contributing to our consult
What motivates you to join LHH as a Software Engineer, and how do you see yourself contributing to our consulting projects?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
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?
Walk me through your professional background and highlight your most complex project.
Walk me through your professional background and highlight your most complex project.
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?
Describe your ideal team environment and the type of engineering culture you thrive in.
Describe your ideal team environment and the type of engineering culture you thrive in.
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 manage your professional development and stay up to date with evolving technologies?
How do you manage your professional development and stay up to date with evolving technologies?
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 approach tracking project requirements, technical documentation, and purchase orders or submittals
How do you approach tracking project requirements, technical documentation, and purchase orders or submittals in a fast-paced project?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How do you balance the need for high-quality, clean code with the pressure of strict project deadlines?
How do you balance the need for high-quality, clean code with the pressure of strict project deadlines?
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 your approach to evaluating third-party tools or bids when deciding on a technical solution for a proj
Explain your approach to evaluating third-party tools or bids when deciding on a technical solution for a project.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Edge instances grow 400 MB per hour until the nightly restart
Edge API instances start at 700 MB resident and grow about 400 MB/hour; a nightly rolling restart has hidden it for weeks. Growth continues unchanged when request rate halves overnight, p99 degrades in the last hours before an instance is recycled, and heap used immediately after a forced full GC rises monotonically. The service holds no product state. Name the discriminating measurement that separates the plausible causes, give the most likely cause, and give the fix and how you would verify it.
Approach
- Separate resident memory from live heap first, because they fail differently. Resident size can grow from fragmentation, native buffers or thread stacks while the heap is flat; heap used after a full GC rising monotonically is the measurement that says objects are reachable and not being released. You already have it, so this is retention, not fragmentation, and that closes off half the candidate list.
- Use the rate's independence from traffic as the discriminator. Growth that continues at half the request rate rules out per-request objects that are merely slow to collect and points at a structure that grows with distinct values observed rather than with call volume. Write the candidates that have that property: a metrics registry keyed on a high-cardinality label, an unevicted cache, an interner, a per-key lock map.
- Take two heap snapshots an hour apart and diff by retained size, reading the dominator tree, not by allocation count or instance count. Expect one root holding a map with millions of entries, then follow the reference chain to the code that inserts and never removes. Allocation profilers point at churn, which is the wrong signal here.
- The candidate that fits this service is an observability label carrying an identifier, such as a request path recorded before templating so that /v1/resources/48213 becomes its own metric series. That grows with distinct ids seen, is independent of rate, and explains the late p99 degradation, since GC cost rises with the size of the live set.
Follow-up
- Post-GC heap is now flat but resident size still creeps. What are you looking at, and does it matter?
- How would you have detected this before an OOM, given the nightly restart masked the trend?
Built from the rounds and topics Lhh candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Lhh loop
- Write out the reported sequence: Recruiter Screening Call, Exploratory and Behavioral Interview, Technical Assessment, Client 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 4 reported rounds, with the weakest marked.
02Work Recruiter/Interview Process Management
- Spend the session on Recruiter/Interview Process Management, which Lhh candidates report being tested on.
- Write one worked example in Recruiter/Interview Process Management and time yourself on it.
Deliverable: One timed worked example in Recruiter/Interview Process Management.
03Work Technical Skills Demonstration
- Spend the session on Technical Skills Demonstration, which Lhh candidates report being tested on.
- Write one worked example in Technical Skills Demonstration and time yourself on it.
Deliverable: One timed worked example in Technical Skills Demonstration.
04Work Problem Solving
- Spend the session on Problem Solving, which Lhh candidates report being tested on.
- Write one worked example in Problem Solving and time yourself on it.
Deliverable: One timed worked example in Problem Solving.
05Answer out loud: Exploratory & Motivation Questions
- Answer aloud, timed: Walk me through your professional background and highlight your most complex project.
- Answer aloud, timed: What motivates you to join LHH as a Software Engineer, and how do you see yourself contributing to our consulting projects?
Deliverable: Spoken answers to 2 reported Exploratory & Motivation Questions question(s), under time.
06Answer out loud: Technical Execution & Project Management
- Answer aloud, timed: How do you approach tracking project requirements, technical documentation, and purchase orders or submittals in a fast-paced project?
- Answer aloud, timed: Describe a time when you identified a potential technical delay in a project. What steps did you take to mitigate the risk and keep the timeline on track?
Deliverable: Spoken answers to 2 reported Technical Execution & Project Management question(s), under time.
07Answer out loud: Behavioral & Client Alignment
- Answer aloud, timed: Tell me about a time you had to explain a complex technical concept to a non-technical client or stakeholder. How did you ensure they understood?
- Answer aloud, timed: How do you handle a situation where a client or product manager requests a feature that you believe is technically unfeasible within the current architecture?
Deliverable: Spoken answers to 2 reported Behavioral & Client Alignment question(s), under time.
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Behavioural rounds judge the decision you made and what it cost.
Describe a time when you identified a potential technical delay in a project. What steps did you take to mitig
Describe a time when you identified a potential technical delay in a project. What steps did you take to mitigate the risk and keep the timeline on track?
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 explain a complex technical concept to a non-technical client or stakeholder.
Tell me about a time you had to explain a complex technical concept to a non-technical client or stakeholder. How did you ensure they understood?
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 a situation where a client or product manager requests a feature that you believe is technic
How do you handle a situation where a client or product manager requests a feature that you believe is technically unfeasible within the current architecture?
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 situation where you had to quickly adapt to a new technology stack or development environment. What
Describe a situation where you had to quickly adapt to a new technology stack or development environment. What was your strategy?
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 constructive feedback from peers or clients during a code review or project retrospective?
How do you handle constructive feedback from peers or clients during a code review or project retrospective?
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
Describe a time when you identified a potential technical delay in a project. What steps did you take to mitigate the risk and keep the timeline on track?
- 02
Tell me about a time you had to explain a complex technical concept to a non-technical client or stakeholder. How did you ensure they understood?
- 03
How do you handle a situation where a client or product manager requests a feature that you believe is technically unfeasible within the current architecture?
- 04
Describe a situation where you had to quickly adapt to a new technology stack or development environment. What was your strategy?
How long does the hiring process typically take at LHH?
The timeline can vary depending on the specific role, location, and whether it is an internal or client-facing position. On average, the process spans three to six weeks from the initial recruiter screen to the final decision.
Lhh Software Engineer candidate reports ↗What is the technical interview format?
You can expect a mix of conceptual technical discussions, project walk-throughs, and practical problem-solving scenarios. The focus is on your approach to solving real-world engineering challenges rather than rote memorization of algorithms.
Lhh Software Engineer candidate reports ↗Will I be interviewing directly with LHH's clients?
If you are applying for a consulting-focused role, a client interview is a standard and crucial part of the process. This meeting is designed to ensure your technical skills and working style align perfectly with the client's project environment.
Lhh Software Engineer candidate reports ↗What is the remote work policy for Software Engineers?
LHH offers a range of working models, including remote, hybrid, and onsite options, depending on the specific team requirements and client commitments. You should clarify the expectations for your target role during the initial recruiter screen.
Lhh Software Engineer candidate reports ↗What topics does Lhh test in interviews?
Lhh interviews most often cover Stakeholder Management, Product Management, Project Management, Marketing Analytics, and Financial Analysis. The exact emphasis depends on the specific role you apply for.
Lhh 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.
- 01Lhh 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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