As a Software Engineer at TotalEnergies, you are at the intersection of traditional energy operations and the digital transformation of a global energy leader. Your work directly impacts the company’s ability to optimize complex systems, ranging from renewable energy parks and wind farms to deep-sea subsea operations. You are not just writing code; you are building the digital infrastructure that enables a massive, multi-national corporation to transition toward cleaner, more efficient energy production. This role requires a high degree of technical versatility and the ability to solve problems in high-stakes environments. You will collaborate with multidisciplinary teams—including researchers, business developers, and operational engineers—to translate complex physical-world challenges into scalable software solutions. Whether you are working on simulation tools, data analysis platforms, or operational monitoring systems, your contributions are critical to the company's long-term sustainability goals. The environment is intellectually stimulating and requires a balance between rigorous technical expertise and a pragmatic, business-oriented mindset. You will often work on projects with significant real-world impact, meaning your code and system designs must be robust, reliable, and capable of operating under the unique constraints of the energy sector.
Application Review
reportedInitial review of submitted applications to assess candidate qualifications.
What to demonstrate
- Initial review of submitted applications to assess candidate qualifications
- Depth in Software Engineering (general)
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 Behavioral Screen
reportedScreening interview led by HR representatives focusing on behavioral fit.
What to demonstrate
- Screening interview led by HR representatives focusing on behavioral fit
- Depth in Software Engineering (general)
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 hr behavioral screen above and write down what you would ask to confirm before it.
Technical Evaluation
reportedIn-depth technical assessments conducted by technical leads to evaluate skills.
What to demonstrate
- In-depth technical assessments conducted by technical leads to evaluate skills
- Depth in Software Engineering (general)
How to prepare
- Answer aloud and timed: What are your long-term career ambitions and how do they align with this role?
- Answer aloud and timed: Describe the architecture of a project you are particularly proud of.
Manager Interview
reportedInterview with senior managers to assess fit within the team and organization.
What to demonstrate
- Interview with senior managers to assess fit within the team and organization
- Depth in Software Engineering (general)
How to prepare
- Prepare two projects you led end to end, each with the decision you owned and what it cost.
- Have three questions about the team's roadmap and how success is measured in the first six months.
3 candidate reports. Individual accounts describe a particular role and hiring cycle.
TotalEnergies Software Engineer interview: technical rounds and communication assessment
The process had several interviews, each with a fairly clear purpose. I began with HR, discussing my background and motivation. Technical interviews with the hiring team came next, followed later by leadership-level conversations. The atmosphere stayed professional and constructive, and I never felt dismissed. There was also an online soft-skills assessment. The in-person rounds combined technica…
Read full experienceTotalEnergies Software Engineer interview: four-step process
The hiring process felt organized from the beginning and had four steps. I started with an HR conversation about my background, motivation, and whether I matched what the company wanted. That was followed by two technical interviews intended to assess my skills in a more hands-on way. The final conversation was with a Product Manager. We moved to the functional side of the role: their expectation…
Read full experienceTotalEnergies Software Engineer interview: assessment centre with group discussion and essay
My process was an assessment-centre-style loop rather than a single interview. After initial contact, I had a multi-part day with several sections, structured as a full evaluation instead of a casual conversation. The centerpiece was a competency-based interview about how I handled past situations and fit the role. There was also a group discussion and a short written essay on a given topic. It f…
Read full experiencePracHub editorial advice for the preparation topics above.
Research the Business Unit
TotalEnergies is massive. Ensure you understand the specific branch (e.g., Renewables, Exploration & Production) you are interviewing for.
Prepare for "Safety" Questions
If your role touches upon operational systems, safety is a non-negotiable value. Always frame your technical decisions with safety and reliability in mind.
Structure Your Answers
Use the STAR method (Situation, Task, Action, Result) for behavioral questions to keep your responses concise and impactful.
Prepare Questions for Them
Always ask insightful questions about the company’s digital strategy or the team’s current challenges to demonstrate genuine interest.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
How do you approach the design of a system when requirements are ambiguous?
How do you approach the design of a system when requirements are ambiguous?
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?
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?
Stop tag and share joins from fanning out a page
resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.
Approach
- Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
- Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
- Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
- Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.
Follow-up
- The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
- A resource can be shared with the same user twice under different permissions. Does your count change, and should it?
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?
Describe the architecture of a project you are particularly proud of.
Describe the architecture of a project you are particularly proud of.
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?
Can you explain how you would handle [specific technology] in a production environment?
Can you explain how you would handle [specific technology] in a production 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?
How do you ensure the safety and reliability of your software in critical operational systems?
How do you ensure the safety and reliability of your software in critical operational systems?
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 us through a technical problem you solved that required deep analytical thinking.
Walk us through a technical problem you solved that required deep analytical thinking.
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?
Listing latency scales with page size, not with filters
The tenant listing endpoint reads resource filtered by tenant_id and status, ordered by updated_at DESC, and returns each row plus the owner's display name from app_user and the actor of that resource's latest resource_revision. p99 is 55 ms at 10 rows per page and 1.4 s at 200. Database telemetry shows 401 statements per request, each under 1 ms, and nothing in the slow-query log. Diagnose the cause and give the fix, stating the statement count per request and the p99 you expect afterwards.
Approach
- Read the counters before forming a theory. 401 statements for 200 rows is one driver query plus two per row, and sub-millisecond execution with an empty slow-query log rules out a bad plan. The time is round trips, which is why it is invisible in every per-query metric and scales with rows returned rather than with filter selectivity.
- Name the two per-row statements from their normalised text: a single-row app_user lookup by user_id, and a resource_revision lookup by resource_id ordered by version DESC LIMIT 1. Confirm by dropping those two response fields and watching the statement count fall to one. That locates the calls in the serialisation layer, not the repository.
- Check that the arithmetic accounts for the whole gap. Measure one round trip to the replica in isolation; 400 trips at roughly 3 ms of network plus 0.2 ms of execution is about 1.3 s on top of a 55 ms baseline, which matches. If the multiplication had fallen short, the N+1 would only be part of the story and you would keep looking.
- Batch both lookups. Collect owner_user_ids and resource_ids from the driver query, then issue WHERE tenant_id = $1 AND user_id = ANY($2) for the users, and PostgreSQL's SELECT DISTINCT ON (resource_id) ... WHERE resource_id = ANY($2) ORDER BY resource_id, version DESC for the latest revision, which the UNIQUE (resource_id, version) index serves directly. On an engine without DISTINCT ON, use a lateral join or a row_number window. Three statements per request at any page size.
Follow-up
- The page size is capped at 200 today. What breaks first if it is raised to 2,000, and is it still this bug?
- How do you stop the next N+1 from reaching production, given that no individual query is slow and the endpoint's tests pass?
Built from the rounds and topics TotalEnergies candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the TotalEnergies loop
- Write out the reported sequence: Application Review, HR Behavioral Screen, Technical Evaluation, Manager 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 Software Engineering (general)
- Spend the session on Software Engineering (general), which TotalEnergies candidates report being tested on.
- Write one worked example in Software Engineering (general) and time yourself on it.
Deliverable: One timed worked example in Software Engineering (general).
03Work Java
- Spend the session on Java, which TotalEnergies candidates report being tested on.
- Write one worked example in Java and time yourself on it.
Deliverable: One timed worked example in Java.
04Work HR Interview Techniques (Behavioral)
- Spend the session on HR Interview Techniques (Behavioral), which TotalEnergies candidates report being tested on.
- Write one worked example in HR Interview Techniques (Behavioral) and time yourself on it.
Deliverable: One timed worked example in HR Interview Techniques (Behavioral).
05Answer out loud: Behavioral and Cultural Alignment
- Answer aloud, timed: Tell us about yourself and your professional journey.
- Answer aloud, timed: Why do you want to work for TotalEnergies specifically?
Deliverable: Spoken answers to 2 reported Behavioral and Cultural Alignment question(s), under time.
06Answer out loud: Technical and Domain Knowledge
- Answer aloud, timed: Describe the architecture of a project you are particularly proud of.
- Answer aloud, timed: How do you approach the design of a system when requirements are ambiguous?
Deliverable: Spoken answers to 2 reported Technical and Domain Knowledge question(s), under time.
07Dry run for TotalEnergies
- Run one full mock under time, then write down the two questions you most want to ask your interviewers.
Deliverable: A completed timed mock and two questions to ask.
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.
Tell us about yourself and your professional journey.
Tell us about yourself and your professional journey.
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?
Why do you want to work for TotalEnergies specifically?
Why do you want to work for TotalEnergies specifically?
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 conflict or disagreement within a cross-functional team?
How do you handle conflict or disagreement within a cross-functional team?
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?
Can you describe a time you had to work under significant pressure or in a stressful environment?
Can you describe a time you had to work under significant pressure or in a stressful environment?
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 are your long-term career ambitions and how do they align with this role?
What are your long-term career ambitions and how do they align with this 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?
- 01
Tell us about yourself and your professional journey.
- 02
Why do you want to work for TotalEnergies specifically?
- 03
How do you handle conflict or disagreement within a cross-functional team?
- 04
Can you describe a time you had to work under significant pressure or in a stressful environment?
How difficult are the technical interviews?
The difficulty is moderate, but the focus is on your specific experience. You won't necessarily face "leetcode" style puzzles; instead, expect questions about the projects you have worked on and how you handle real-world engineering challenges.
TotalEnergies Software Engineer candidate reports ↗What is the most important part of the interview?
The discussion with the hiring manager is often the most critical stage. This is where they assess your technical depth, your problem-solving style, and your potential to grow within the company.
TotalEnergies Software Engineer candidate reports ↗Is there a personality test?
Yes, many candidates report taking personality or psychometric tests early in the process. Answer these honestly; they are used to determine if your working style aligns with the team’s needs.
TotalEnergies Software Engineer candidate reports ↗How long does the process take?
It can vary significantly, ranging from three weeks to several months. While many processes move quickly, large organizations can have administrative delays, so maintain regular, polite communication with your recruiter.
TotalEnergies Software Engineer candidate reports ↗What topics does TotalEnergies test in interviews?
TotalEnergies interviews most often cover Stakeholder Communication, Problem Solving, Python, Data Analysis, and Cross-functional Collaboration. The exact emphasis depends on the specific role you apply for.
TotalEnergies 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.
- 01TotalEnergies 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
Explore related engineering environments and compare the preparation focus.
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