Rhombus Power Software Engineer Interview Guide

The 60-second brief

As a Software Engineer at Rhombus Power, you are at the intersection of high-stakes systems architecture and mission-critical engineering. The role is pivotal in building and maintaining the infrastructure that powers the company’s complex technical ecosystem. You are not just writing code; you are designing robust, scalable solutions that directly impact how the organization processes data and delivers value to its clients. Working here requires a balance of technical precision and architectural foresight. You will often find yourself tasked with migrating legacy stacks to modern, containerized environments, ensuring that your deliverables are fully integrated and performant.

This guide is scoped to a Software Engineer candidate at Rhombus Power.

Focus areas

• Migration to a New Stack
• Containerization (Containers)
• Deployment Automation

The Rhombus Power interview process

Rhombus Power candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Initial Screening

The first step involves a preliminary assessment to gauge candidate fit.

What to demonstrate

• The first step involves a preliminary assessment to gauge candidate fit
• Depth in Migration to a New Stack

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 Deep Dives

A series of in-depth technical interviews focusing on coding skills and engineering trade-offs.

What to demonstrate

• A series of in-depth technical interviews focusing on coding skills and engineering trade-offs
• Depth in Migration to a New Stack

How to prepare

• Answer aloud and timed: How do you optimize a SQL query to handle high-volume data requests?
• Answer aloud and timed: What are the key considerations when designing a scalable backend service?

Conversation with Leadership

Final discussion with leadership to assess overall alignment with company values and goals.

What to demonstrate

• Final discussion with leadership to assess overall alignment with company values and goals
• Depth in Migration to a New Stack

How to prepare

• Answer aloud and timed: How do you debug a production-level issue in a distributed system?
• Answer aloud and timed: Solve a standard algorithmic problem involving data structures like arrays or strings.

Where candidates lose points

Prepare for the "Why

Don't just show that you can code a solution; be ready to explain why you chose a specific tool or architectural pattern over alternatives.

Be ready for scheduling changes

If an interview is rescheduled, stay professional and flexible. It often reflects the busy nature of the engineering team rather than a lack of interest in your candidacy.

Focus on the stack

If you know the team is migrating to a new stack, research the technologies involved in that migration to show alignment with their current engineering goals.

Articulate your process

During coding rounds, think out loud. The interviewer is interested in how you navigate dead ends as much as how you reach the final solution.

Questions & practice

Solve a standard algorithmic problem involving data structures like arrays or strings.

Medium · Coding and Problem Solving

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. 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?

Implement a basic frontend component or feature from scratch.

Medium · Coding and Problem Solving

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. 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?

Describe your process for refactoring a piece of code to improve readability and performance.

Medium · Coding and Problem Solving

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. 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?

How do you approach testing your code to ensure edge cases are handled?

Medium · Coding and Problem Solving

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. 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?

Write a script to automate a repetitive deployment task.

Medium · Coding and Problem Solving

Approach

1. Restate the input: its shape, its size, and what is guaranteed about it.
2. Name the brute-force solution and its complexity before improving on it.
3. Choose the data structure from the access pattern, not from familiarity.
4. 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?

How do you optimize a SQL query to handle high-volume data requests?

Medium · Technical and Domain Proficiency

Approach

1. Name the grain you start from and join outward from it.
2. Check whether any join is one-to-many before aggregating, or the sums inflate.
3. Say which index the query would use, and what makes it unusable.
4. 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?

Write the update path that detects a concurrent edit

Medium · optimistic concurrency · transactional outbox · audit history

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

1. 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.
2. 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.
3. 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.
4. 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?

How would you approach deploying a fully containerized, connected deliverable?

Medium · Technical and Domain Proficiency

Approach

1. Clarify what is being asked and what a complete answer contains.
2. State your assumptions explicitly before working the problem.
3. Say what you would check first and why it is the highest-information step.
4. 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 the pros and cons of migrating a legacy system to a containerized architecture?

Medium · Technical and Domain Proficiency

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. State the consistency you need, and where you are willing to be stale.

Follow-up

• What breaks first when traffic grows ten times?
• How does this behave when that dependency is down for an hour?

What are the key considerations when designing a scalable backend service?

Medium · Technical and Domain Proficiency

Approach

1. Fix the scope first: who calls this, how often, and what they do when it fails.
2. Name the read and write paths separately; they rarely have the same bottleneck.
3. Choose a partition key and say what query it makes expensive.
4. State the consistency you need, and where you are willing to be stale.

Follow-up

• What breaks first when traffic grows ten times?
• How does this behave when that dependency is down for an hour?

How do you debug a production-level issue in a distributed system?

Medium · Technical and Domain Proficiency

Approach

1. Establish what changed and when, before forming any theory.
2. Pick a bisection that eliminates candidates whichever way it turns out.
3. Check the instrumentation before believing the symptom.
4. 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?

Suggested practice checklist

Built from the rounds and topics Rhombus Power candidates report.

Day 1 — Map the Rhombus Power loop

• Write out the reported sequence: Initial Screening, Technical Deep Dives, Conversation with Leadership.
• 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 3 reported rounds, with the weakest marked.

Day 2 — Work Migration to a New Stack

• Spend the session on Migration to a New Stack, which Rhombus Power candidates report being tested on.
• Write one worked example in Migration to a New Stack and time yourself on it.

Deliverable: One timed worked example in Migration to a New Stack.

Day 3 — Work Containerization (Containers)

• Spend the session on Containerization (Containers), which Rhombus Power candidates report being tested on.
• Write one worked example in Containerization (Containers) and time yourself on it.

Deliverable: One timed worked example in Containerization (Containers).

Day 4 — Work Deployment Automation

• Spend the session on Deployment Automation, which Rhombus Power candidates report being tested on.
• Write one worked example in Deployment Automation and time yourself on it.

Deliverable: One timed worked example in Deployment Automation.

Day 5 — Answer out loud: Technical and Domain Proficiency

• Answer aloud, timed: How would you approach deploying a fully containerized, connected deliverable?
• Answer aloud, timed: Can you explain the pros and cons of migrating a legacy system to a containerized architecture?

Deliverable: Spoken answers to 2 reported Technical and Domain Proficiency question(s), under time.

Day 6 — Answer out loud: Coding and Problem Solving

• Answer aloud, timed: Solve a standard algorithmic problem involving data structures like arrays or strings.
• Answer aloud, timed: Implement a basic frontend component or feature from scratch.

Deliverable: Spoken answers to 2 reported Coding and Problem Solving question(s), under time.

Day 7 — Answer out loud: Behavioral and Culture Fit

• Answer aloud, timed: Tell me about a time you had to learn a new technology quickly to meet a deadline.
• Answer aloud, timed: How do you handle feedback on your code from senior engineers or stakeholders?

Deliverable: Spoken answers to 2 reported Behavioral and Culture Fit question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

Tell me about a time you had to learn a new technology quickly to meet a deadline.

Medium · Behavioral and Culture Fit

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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 on your code from senior engineers or stakeholders?

Medium · Behavioral and Culture Fit

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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 project you owned from start to finish.

Medium · Behavioral and Culture Fit

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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 manage your time when juggling multiple technical priorities?

Medium · Behavioral and Culture Fit

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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 contribute to the mission at Rhombus Power?

Medium · Behavioral and Culture Fit

Approach

1. Pick a story where you made the decision, not one where you watched it.
2. State the situation in two sentences and spend the rest on the reasoning.
3. Give the blast radius: what could have broken, and what you measured.
4. 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?