The Software Engineer role at the joint venture between LG Energy Solution and Honda sits at the critical intersection of advanced battery manufacturing and automotive innovation. You are responsible for developing the digital infrastructure and software systems that power high-capacity battery production. This role is essential to ensuring that manufacturing processes are optimized, automated, and scalable to meet the global demand for electric vehicle energy storage. Your impact centers on the reliability and efficiency of the production line. By building robust software solutions, you directly influence the quality and consistency of battery modules that will power the next generation of Honda electric vehicles. You will work in a high-stakes environment where software performance directly correlates to physical output, making this an ideal position for engineers who enjoy seeing their code manifest in tangible, large-scale industrial results. ##### Tip This role is based in Jeffersonville, Ohio. Candidates should prepare to work in a collaborative, mission-driven environment where cross-functional communication between software, mechanical, and electrical teams is a daily expectation.
Initial Screening
reportedAssessment of candidate fit for the role and company.
What to demonstrate
- Assessment of candidate fit for the role and company
- Depth in Software Engineering
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 Interviews
reportedIn-depth discussions on background and problem-solving capabilities.
What to demonstrate
- In-depth discussions on background and problem-solving capabilities
- Depth in Software Engineering
How to prepare
- Answer aloud and timed: What experience do you have with PLC (Programmable Logic Controller) programming or industrial automation software?
- Answer aloud and timed: How do you ensure data integrity and system security when connecting factory floor equipment to a central network?
PracHub editorial advice for the preparation topics above.
Understand the "Why
Don't just list technical skills; explain how they contribute to the reliability of a factory floor.
Prepare for Ambiguity
If you are given a hypothetical scenario, ask clarifying questions to narrow down the constraints before jumping into a solution.
Practice STAR
Use the Situation, Task, Action, Result framework for all your behavioral answers to keep them concise and impactful.
Do not underestimate the importance of safety
Even as a software engineer, you must demonstrate an awareness of how code changes impact physical safety and equipment longevity.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Describe a situation where you encountered a significant technical roadblock. What steps did you take to resol
Describe a situation where you encountered a significant technical roadblock. What steps did you take to resolve it?
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?
Diff a projection against the primary without per-row point reads
The listing projection has drifted and some rows show a stale version. The primary holds 40,000,000 resource rows across 12,000 tenants while serving 1,200 writes and 14,000 reads per second. The obvious repair, reading each resource row and comparing its version against the projection, is correct and would eventually finish. Explain precisely why it is unacceptable here, then give a diff that finds the differing rows, state its complexity, and make it safe to run against a live primary. Replication lag is usually under 100 ms and is not bounded.
Approach
- Quantify the naive cost rather than calling it slow: 40,000,000 point reads at even 0.5 ms each is over five hours serialised, and the only lever is concurrency, which is exactly what you cannot spend. The primary's pool is sized for the write path, and 40,000,000 random reads evict the buffer cache that sustains the 85 percent cache hit rate, so the audit degrades the system it is auditing.
- Replace random access with one ordered pass per side. Both sides can be read in (tenant_id, resource_id) order, which is a sequential scan on each and a merge join in O(n) time and O(1) memory. For a dense diff that is the whole answer, and it reads the primary once instead of 40,000,000 times.
- For the expected sparse case, compare range hashes instead of rows: partition the key space, compute per range an order-independent aggregate over hash(resource_id, version), compare aggregates, and descend only into ranges that differ. With d differing rows and branching factor B, at most d ranges mismatch per level, so the drill-down examines O(d log_B(n/d)) ranges and reads full rows only in mismatching leaves.
- Aggregate with a sum modulo 2^64 or a multiset hash, never XOR. XOR is order-independent but self-cancelling, so two rows wrong in the same way, or a row duplicated on one side, leave the range aggregate matching and the range is declared clean.
Follow-up
- The diff reports 900 stale rows. How do you decide between patching those rows and rebuilding the projection from resource_revision?
- Same job, but the projection lives in a search index that cannot be scanned in key order. What changes?
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?
Denormalise tenant onto revisions and backfill it live
resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.
Approach
- Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
- Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
- Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
- Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.
Follow-up
- The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
- How do you verify the backfill actually finished, given rows are still being inserted while it runs?
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?
Can you explain your process for integrating software systems with existing hardware or machinery?
Can you explain your process for integrating software systems with existing hardware or machinery?
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
What experience do you have with PLC (Programmable Logic Controller) programming or industrial automation soft
What experience do you have with PLC (Programmable Logic Controller) programming or industrial automation software?
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 data integrity and system security when connecting factory floor equipment to a central netw
How do you ensure data integrity and system security when connecting factory floor equipment to a central network?
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 debugging complex software issues in a live, real-time manufacturing environment?
How do you approach debugging complex software issues in a live, real-time manufacturing 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 LG Energy Solution and Honda candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the LG Energy Solution and Honda loop
- Write out the reported sequence: Initial Screening, Technical Interviews.
- 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 2 reported rounds, with the weakest marked.
02Work Software Engineering
- Spend the session on Software Engineering, which LG Energy Solution and Honda candidates report being tested on.
- Write one worked example in Software Engineering and time yourself on it.
Deliverable: One timed worked example in Software Engineering.
03Work Engineering Problem Solving
- Spend the session on Engineering Problem Solving, which LG Energy Solution and Honda candidates report being tested on.
- Write one worked example in Engineering Problem Solving and time yourself on it.
Deliverable: One timed worked example in Engineering Problem Solving.
04Work Programming (General)
- Spend the session on Programming (General), which LG Energy Solution and Honda candidates report being tested on.
- Write one worked example in Programming (General) and time yourself on it.
Deliverable: One timed worked example in Programming (General).
05Answer out loud: Technical & Domain Knowledge
- Answer aloud, timed: How do you approach debugging complex software issues in a live, real-time manufacturing environment?
- Answer aloud, timed: Can you explain your process for integrating software systems with existing hardware or machinery?
Deliverable: Spoken answers to 2 reported Technical & Domain Knowledge question(s), under time.
06Answer out loud: Behavioral & Situational
- Answer aloud, timed: Tell me about a time you had to explain a complex technical problem to a non-technical stakeholder.
- Answer aloud, timed: How do you prioritize your workload when managing multiple engineering projects simultaneously?
Deliverable: Spoken answers to 2 reported Behavioral & Situational question(s), under time.
07Dry run for LG Energy Solution and Honda
- 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.
Describe a time you had to optimize a piece of software to improve production throughput or reduce latency.
Describe a time you had to optimize a piece of software to improve production throughput or reduce latency.
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 problem to a non-technical stakeholder.
Tell me about a time you had to explain a complex technical problem to a non-technical stakeholder.
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 workload when managing multiple engineering projects simultaneously?
How do you prioritize your workload when managing multiple engineering projects simultaneously?
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 are you interested in the intersection of energy storage technology and software engineering?
Why are you interested in the intersection of energy storage technology and software engineering?
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 feedback from cross-functional teams, such as mechanical or facilities engineers?
How do you handle feedback from cross-functional teams, such as mechanical or facilities engineers?
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 you had to optimize a piece of software to improve production throughput or reduce latency.
- 02
Tell me about a time you had to explain a complex technical problem to a non-technical stakeholder.
- 03
How do you prioritize your workload when managing multiple engineering projects simultaneously?
- 04
Why are you interested in the intersection of energy storage technology and software engineering?
How much time should I spend preparing for the technical portion?
Dedicate at least 10–15 hours to reviewing your past projects and familiarizing yourself with industrial automation concepts. Focus on being able to explain the "why" behind your technical decisions.
LG Energy Solution and Honda Software Engineer candidate reports ↗Is this a remote role?
No, this role is based in Jeffersonville, OH, as it requires hands-on collaboration with the manufacturing floor and physical equipment.
LG Energy Solution and Honda Software Engineer candidate reports ↗What differentiates top candidates?
Top candidates are those who show curiosity about the battery manufacturing process itself, not just the software. Showing interest in how your code supports the broader mission of LG Energy Solution and Honda will set you apart.
LG Energy Solution and Honda Software Engineer candidate reports ↗What topics does LG Energy Solution and Honda test in interviews?
LG Energy Solution and Honda interviews most often cover Quality Assurance (QA), Software Engineering, Factory Automation, Engineering Problem Solving, and Equipment Engineering (Industrial). The exact emphasis depends on the specific role you apply for.
LG Energy Solution and Honda 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.
- 01LG Energy Solution and Honda 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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