A Software Engineer at Stem plays a pivotal role in driving the transition to a clean energy future. Stem is a pioneer in AI-driven energy storage and optimization, and the software engineering team is responsible for building and scaling the intelligent platforms that manage these complex energy assets. As a Software Engineer, you will work on the core services, backend APIs, and data pipelines that power Stem's flagship Athena smart energy software, directly impacting how commercial, industrial, and utility-scale customers optimize their energy usage. The work you do here has a direct, real-world impact on grid stability and carbon reduction. This is not just a standard backend role; it is an opportunity to solve highly complex, real-time data challenges at the intersection of software, IoT hardware, and green energy markets. You will build resilient systems that ingest massive amounts of telemetry data, execute optimization algorithms, and control physical battery storage systems in real time. To succeed in this role, you must be comfortable navigating distributed systems, building robust APIs, and collaborating with cross-functional teams. looks for engineers who are not only technically sound but also deeply passionate about sustainability and renewable energy. The engineering culture values practicality, clean code practices, and a collaborative approach to solving some of the most pressing challenges in clean technology. Stem
Recruiter Screen
reportedInitial conversation with a recruiter to discuss your background and fit for the role.
What to demonstrate
- Initial conversation with a recruiter to discuss your background and fit for the role
- Depth in API Development
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.
Hiring Manager Conversation
reportedDiscussion with the hiring manager about your background and technical interests.
What to demonstrate
- Discussion with the hiring manager about your background and technical interests
- Depth in API Development
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.
Take-Home Assignment
reportedComplete a coding assignment to showcase your coding style and architectural patterns.
What to demonstrate
- Complete a coding assignment to showcase your coding style and architectural patterns
- Depth in API Development
How to prepare
- Answer aloud and timed: What are the key differences between synchronous and asynchronous message processing, and when would you choose one over the other in a distributed system?
- Answer aloud and timed: How would you design a system that ingests high-frequency data from battery storage units and processes it for real-time monitoring?
Panel Interview
reportedMeet with several engineering team members to review your assignment and discuss system design.
What to demonstrate
- Meet with several engineering team members to review your assignment and discuss system design
- Depth in API Development
How to prepare
- Answer aloud and timed: Describe how you would handle partial failures or network latency when communicating with external energy grid APIs.
- Answer aloud and timed: How do you approach database schema migrations in a high-availability production environment without causing downtime?
PracHub editorial advice for the preparation topics above.
Prioritize Clean Code in the Take-Home
The engineering team places a high value on software design. Ensure your take-home assignment is well-structured, uses proper naming conventions, includes robust error handling, and features comprehensive unit tests.
Showcase Your Passion for Clean Tech
Stem employees are deeply committed to the renewable energy mission. Take some time to research current trends in energy storage and smart grid technology, and be ready to share why you want to apply your engineering skills to this industry.
Prepare for Cross-Functional Discussions
Because your panel interview will include directors and engineers from QA and DevOps, be prepared to discuss how you ensure your code is easy to test, monitor, and deploy.
Communicate Your Trade-Offs
When discussing system design or your take-home assignment, always explain the "why" behind your technical decisions. Acknowledging the trade-offs of your chosen approach demonstrates mature engineering judgment.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
How do you handle database concurrency and race conditions when multiple services attempt to update the same r
How do you handle database concurrency and race conditions when multiple services attempt to update the same resource simultaneously?
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?
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?
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?
How do you approach database schema migrations in a high-availability production environment without causing d
How do you approach database schema migrations in a high-availability production environment without causing downtime?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
What strategies do you use to optimize database query performance when retrieving large volumes of historical
What strategies do you use to optimize database query performance when retrieving large volumes of historical time-series data?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
How do you design a scalable RESTful API to handle real-time telemetry data from thousands of IoT devices?
How do you design a scalable RESTful API to handle real-time telemetry data from thousands of IoT devices?
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?
Explain the principles of clean architecture and how you apply them when structuring a new backend service.
Explain the principles of clean architecture and how you apply them when structuring a new backend service.
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?
Describe your approach to writing comprehensive unit and integration tests for a newly developed API endpoint.
Describe your approach to writing comprehensive unit and integration tests for a newly developed API endpoint.
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 are the key differences between synchronous and asynchronous message processing, and when would you choos
What are the key differences between synchronous and asynchronous message processing, and when would you choose one over the other in a distributed system?
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 design a system that ingests high-frequency data from battery storage units and processes it for
How would you design a system that ingests high-frequency data from battery storage units and processes it for real-time monitoring?
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?
Describe how you would handle partial failures or network latency when communicating with external energy grid
Describe how you would handle partial failures or network latency when communicating with external energy grid APIs.
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?
Read latency spikes on a sixty-second sawtooth
The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.
Approach
- Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
- Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
- Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
- De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.
Follow-up
- The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
- How does your answer change if the recompute takes 4 seconds instead of 250 ms?
Built from the rounds and topics Stem candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Stem loop
- Write out the reported sequence: Recruiter Screen, Hiring Manager Conversation, Take-Home Assignment, Panel 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 API Development
- Spend the session on API Development, which Stem candidates report being tested on.
- Write one worked example in API Development and time yourself on it.
Deliverable: One timed worked example in API Development.
03Work .NET (Latest Framework)
- Spend the session on .NET (Latest Framework), which Stem candidates report being tested on.
- Write one worked example in .NET (Latest Framework) and time yourself on it.
Deliverable: One timed worked example in .NET (Latest Framework).
04Work Coding Exercises (Practical Implementation)
- Spend the session on Coding Exercises (Practical Implementation), which Stem candidates report being tested on.
- Write one worked example in Coding Exercises (Practical Implementation) and time yourself on it.
Deliverable: One timed worked example in Coding Exercises (Practical Implementation).
05Answer out loud: Backend Development & API Design
- Answer aloud, timed: How do you design a scalable RESTful API to handle real-time telemetry data from thousands of IoT devices?
- Answer aloud, timed: Explain the principles of clean architecture and how you apply them when structuring a new backend service.
Deliverable: Spoken answers to 2 reported Backend Development & API Design question(s), under time.
06Answer out loud: System Integration & Architecture
- Answer aloud, timed: How would you design a system that ingests high-frequency data from battery storage units and processes it for real-time monitoring?
- Answer aloud, timed: Describe how you would handle partial failures or network latency when communicating with external energy grid APIs.
Deliverable: Spoken answers to 2 reported System Integration & Architecture question(s), under time.
07Answer out loud: Behavioral & Mission Alignment
- Answer aloud, timed: Why are you interested in working in the renewable energy and energy storage industry?
- Answer aloud, timed: Describe a time when you had to collaborate with cross-functional teams, such as QA or DevOps, to resolve a critical production issue.
Deliverable: Spoken answers to 2 reported Behavioral & Mission Alignment 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 working in the renewable energy and energy storage industry?
Why are you interested in working in the renewable energy and energy storage industry?
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 time when you had to collaborate with cross-functional teams, such as QA or DevOps, to resolve a cr
Describe a time when you had to collaborate with cross-functional teams, such as QA or DevOps, to resolve a critical production issue.
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 make a technical trade-off to meet a tight project deadline. What was the outc
Tell me about a time you had to make a technical trade-off to meet a tight project deadline. What was the outcome?
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 receiving critical feedback on your code during a peer review?
How do you handle receiving critical feedback on your code during a peer review?
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 working in the renewable energy and energy storage industry?
- 02
Describe a time when you had to collaborate with cross-functional teams, such as QA or DevOps, to resolve a critical production issue.
- 03
Tell me about a time you had to make a technical trade-off to meet a tight project deadline. What was the outcome?
- 04
How do you handle receiving critical feedback on your code during a peer review?
What is the typical tech stack for a Software Engineer at Stem?
While Stem utilizes various technologies across different teams, there is a strong emphasis on modern backend frameworks, including.NET/C# for API development, cloud-native services (primarily AWS), and database technologies optimized for both relational and time-series data.
Stem Software Engineer candidate reports ↗How difficult is the technical interview process?
Candidates generally describe the technical interviews as average in difficulty and highly practical. Rather than focusing on complex, theoretical algorithm puzzles, the questions are realistic and centered around API design, clean coding practices, and system integration.
Stem Software Engineer candidate reports ↗What is the format of the take-home coding assignment?
The assignment typically involves building a small, functional API or backend service using industry best practices. It is designed to be completed in a few hours, and the engineering panel will use your submission as the basis for a collaborative technical discussion during the onsite interview.
Stem Software Engineer candidate reports ↗How does Stem evaluate culture fit during the interview process?
Stem looks for candidates who are collaborative, open to feedback, and genuinely passionate about renewable energy. Throughout the process, interviewers will assess your communication style, how you handle technical trade-offs, and your alignment with the company's mission to drive clean energy transition.
Stem Software Engineer candidate reports ↗What is the typical timeline from application to offer?
The entire process can take anywhere from three to six weeks, depending on scheduling availability. This timeline includes the initial recruiter call, the take-home assignment, and the multi-hour panel interview.
Stem Software Engineer candidate reports ↗What topics does Stem test in interviews?
Stem interviews most often cover Behavioral Interviewing, API Development, Business Analysis Fundamentals,.NET (Latest Framework), and Excel (Advanced Spreadsheet Skills). The exact emphasis depends on the specific role you apply for.
Stem 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.
- 01Stem 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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