A Software Engineer at FTI Consulting operates at the intersection of advanced technology, data analytics, and corporate strategy. Unlike traditional technology firms where engineering teams focus solely on consumer-facing products, engineers at FTI Consulting build, optimize, and maintain highly specialized applications used to solve complex, high-stakes business challenges. These challenges include forensic investigations, e-discovery, corporate restructuring, regulatory compliance, and economic modeling. The impact of this role is immediate and profound. The proprietary software and data pipelines you develop will be used by consultants and clients to make sense of massive, unstructured datasets during critical legal disputes or financial crises. Whether you are working within the Technology segment, Forensic Litigation Consulting, or Corporate Finance, your work directly enables the firm to deliver defensible, data-driven insights to global corporations and law firms. This environment requires a unique blend of technical excellence and business acumen. You will not just write code in a silo; you will design scalable architectures, optimize data processing engines, and collaborate directly with domain experts. For a, this translates to a highly stimulating career path characterized by diverse projects, rapid problem-solving, and the opportunity to see your technical solutions directly influence real-world corporate outcomes. Software Engineer
Application Review
reportedInitial review of the candidate's application materials to assess qualifications.
What to demonstrate
- Initial review of the candidate's application materials to assess qualifications
- Depth in Behavioral interview skills
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.
Initial Screening
reportedIncludes a pre-recorded video interview with behavioral and introductory questions.
What to demonstrate
- Includes a pre-recorded video interview with behavioral and introductory questions
- Depth in Behavioral interview skills
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.
HR Phone Screen
reportedA phone interview with HR to discuss the candidate's background and fit.
What to demonstrate
- A phone interview with HR to discuss the candidate's background and fit
- Depth in Behavioral interview skills
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.
Behavioral Interview
reportedInterview with a hiring manager or developer focusing on behavioral aspects.
What to demonstrate
- Interview with a hiring manager or developer focusing on behavioral aspects
- Depth in Behavioral interview skills
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.
Superday
reportedFinal round of comprehensive interviews including technical evaluations and fit discussions.
What to demonstrate
- Final round of comprehensive interviews including technical evaluations and fit discussions
- Depth in Behavioral interview skills
How to prepare
- Answer aloud and timed: Describe your experience with cloud infrastructure (e.g., AWS, Azure) and how you have utilized it in past projects.
- Answer aloud and timed: What are the key principles of designing a secure and scalable RESTful API?
PracHub editorial advice for the preparation topics above.
Prepare for the pre-recorded format
Since the initial screen often uses a pre-recorded video format with strict time limits, practice recording yourself answering common behavioral questions. Focus on delivering clear, structured answers using the STAR method in under 60 seconds.
Brush up on data and databases
Given the data-intensive nature of FTI Consulting's work, expect questions on database design, SQL queries, and data manipulation. Showing strength in these areas is highly valued.
Showcase your consulting aptitude
Highlight experiences where you had to work with stakeholders, gather requirements, or explain technical details to non-technical business partners. This demonstrates that you can thrive in a consulting-adjacent environment.
If you encounter an interviewer who dominates the conversation or moves very quickly, remain calm and professional
Focus on delivering concise, high-value answers when given the opportunity, and use your time to highlight your core strengths clearly.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
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?
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?
Archive a resource graph without breaking live references or recursing
Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.
Approach
- Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
- Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
- Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
- Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.
Follow-up
- The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
- The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?
Write the update path that detects a concurrent edit
resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.
Approach
- One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
- Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
- State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
- Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.
Follow-up
- A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
- Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?
Explain why the owner filter ignores the listing index
The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.
Approach
- Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
- For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
- Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
- Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.
Follow-up
- 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
- A dashboard runs this for 40 owners in one page load. What changes about the design?
Explain the difference between relational and non-relational databases, and when you would choose one over the
Explain the difference between relational and non-relational databases, and when you would choose one over the other.
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 ensure code quality and maintainability in a collaborative development environment?
How do you ensure code quality and maintainability in a collaborative development 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?
Walk me through the life cycle of an HTTP request from the moment a user enters a URL in their browser.
Walk me through the life cycle of an HTTP request from the moment a user enters a URL in their browser.
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 key principles of designing a secure and scalable RESTful API?
What are the key principles of designing a secure and scalable RESTful API?
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 approach analyzing a massive, unstructured dataset to identify anomalies or patterns of fraud?
How would you approach analyzing a massive, unstructured dataset to identify anomalies or patterns of fraud?
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?
Solve this logical reasoning puzzle: [A scenario-based question testing spatial, mathematical, or sequence-bas
Solve this logical reasoning puzzle: [A scenario-based question testing spatial, mathematical, or sequence-based logic].
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 explain a basic statistical concept, such as regression analysis, and how you might implement it in co
Can you explain a basic statistical concept, such as regression analysis, and how you might implement it in code?
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 an algorithm to detect duplicate records across millions of rows of data with minor spell
How would you design an algorithm to detect duplicate records across millions of rows of data with minor spelling variations?
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?
Every query on one table stalls for forty seconds mid-deploy
During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.
Approach
- Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
- Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
- Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
- Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.
Follow-up
- The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
- Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?
Built from the rounds and topics Fti Consulting candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Fti Consulting loop
- Write out the reported sequence: Application Review, Initial Screening, HR Phone Screen, Behavioral Interview, Superday.
- 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 Behavioral interview skills
- Spend the session on Behavioral interview skills, which Fti Consulting candidates report being tested on.
- Write one worked example in Behavioral interview skills and time yourself on it.
Deliverable: One timed worked example in Behavioral interview skills.
03Work Technical interview fundamentals
- Spend the session on Technical interview fundamentals, which Fti Consulting candidates report being tested on.
- Write one worked example in Technical interview fundamentals and time yourself on it.
Deliverable: One timed worked example in Technical interview fundamentals.
04Work Communication under time constraints
- Spend the session on Communication under time constraints, which Fti Consulting candidates report being tested on.
- Write one worked example in Communication under time constraints and time yourself on it.
Deliverable: One timed worked example in Communication under time constraints.
05Answer out loud: Pre-Recorded & Behavioral Screening
- Answer aloud, timed: Why are you interested in joining FTI Consulting, and how does your background align with our technology practice?
- Answer aloud, timed: Describe a challenging technical project you worked on. What was your role, and how did you overcome the primary obstacle?
Deliverable: Spoken answers to 2 reported Pre-Recorded & Behavioral Screening question(s), under time.
06Answer out loud: Broad Technical Concepts & Skillset Review
- Answer aloud, timed: Explain the difference between relational and non-relational databases, and when you would choose one over the other.
- Answer aloud, timed: How do you ensure code quality and maintainability in a collaborative development environment?
Deliverable: Spoken answers to 2 reported Broad Technical Concepts & Skillset Review question(s), under time.
07Answer out loud: Logic, Quantitative, and Problem-Solving
- Answer aloud, timed: How would you approach analyzing a massive, unstructured dataset to identify anomalies or patterns of fraud?
- Answer aloud, timed: Solve this logical reasoning puzzle: [A scenario-based question testing spatial, mathematical, or sequence-based logic].
Deliverable: Spoken answers to 2 reported Logic, Quantitative, and Problem-Solving 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.
Why are you interested in joining FTI Consulting, and how does your background align with our technology pract
Why are you interested in joining FTI Consulting, and how does your background align with our technology practice?
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 challenging technical project you worked on. What was your role, and how did you overcome the prima
Describe a challenging technical project you worked on. What was your role, and how did you overcome the primary obstacle?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
How do you prioritize your tasks when working on multiple projects with competing deadlines?
How do you prioritize your tasks when working on multiple projects with competing deadlines?
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?
Talk about a time you had to explain a complex technical concept to a non-technical stakeholder or team member
Talk about a time you had to explain a complex technical concept to a non-technical stakeholder or team member.
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 areas of technology or software development are you most excited to explore in your next role?
What areas of technology or software development are you most excited to explore in your next role?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Describe your experience with cloud infrastructure (e.g., AWS, Azure) and how you have utilized it in past pro
Describe your experience with cloud infrastructure (e.g., AWS, Azure) and how you have utilized it in past projects.
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
Why are you interested in joining FTI Consulting, and how does your background align with our technology practice?
- 02
Describe a challenging technical project you worked on. What was your role, and how did you overcome the primary obstacle?
- 03
How do you prioritize your tasks when working on multiple projects with competing deadlines?
- 04
Talk about a time you had to explain a complex technical concept to a non-technical stakeholder or team member.
How technical is the interview process for Software Engineers at FTI Consulting?
The technical process is thorough but tends to focus more on broad conceptual knowledge, system design, and practical skills rather than highly abstract, competitive-programming-style algorithms. Be prepared to explain your past projects, discuss architectural tradeoffs, and demonstrate strong logical reasoning.
Fti Consulting Software Engineer candidate reports ↗What is the company culture like for engineering teams?
The culture combines the intellectual rigor of a top-tier consulting firm with the collaborative, problem-solving mindset of a tech team. It is highly professional, fast-paced, and intellectually stimulating, offering engineers exposure to diverse, high-impact business challenges.
Fti Consulting Software Engineer candidate reports ↗How long does the hiring process typically take from application to offer?
The timeline generally ranges from three to six weeks. It usually starts with an automated screen or logic test, followed by HR and hiring manager interviews, and concludes with a final-round interview day.
Fti Consulting Software Engineer candidate reports ↗Does FTI Consulting support remote or hybrid work for Software Engineers?
FTI Consulting typically operates on a hybrid model, combining remote work flexibility with in-office collaboration. The exact expectations depend on the specific office location and team requirements.
Fti Consulting Software Engineer candidate reports ↗What topics does Fti Consulting test in interviews?
Fti Consulting interviews most often cover Data Analysis, Behavioral Interviewing, Behavioral interview skills, Python, and Quantitative Reasoning. The exact emphasis depends on the specific role you apply for.
Fti Consulting 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.
- 01Fti Consulting 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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