A Software Engineer at Truemeds plays a pivotal role in bridging the gap between complex healthcare logistics and seamless user experiences. As the company continues to scale its digital pharmacy platform, your work directly impacts how patients access affordable medication, ensuring that backend systems are robust, performant, and reliable. You are not just writing code; you are building the infrastructure that powers critical health-tech solutions. In this role, you will contribute to high-stakes environments where system architecture and data integrity are paramount. Whether you are optimizing database queries for speed, designing scalable microservices, or ensuring that Java-based applications handle high concurrency, your contributions are the backbone of the Truemeds ecosystem. This position offers the unique opportunity to solve real-world problems in the healthcare domain, requiring a blend of technical precision and a strong sense of ownership over the product. ##### Tip The role requires a high degree of technical versatility. You should be prepared to discuss your current projects with a focus on system flow and the reasoning behind your architectural choices.
Recruiter Screen
reportedInitial screening to evaluate candidate fit and discuss the role.
What to demonstrate
- Initial screening to evaluate candidate fit and discuss the role
- Depth in Coding and Problem Solving
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 Rounds
reportedOne or more rounds assessing coding challenges, system design, and previous experience.
What to demonstrate
- One or more rounds assessing coding challenges, system design, and previous experience
- Depth in Coding and Problem Solving
How to prepare
- Answer aloud and timed: What are the key differences between various Java garbage collection algorithms?
- Answer aloud and timed: How do you manage transaction management within a Spring Boot application?
PracHub editorial advice for the preparation topics above.
Structure your answers
Use the STAR method (Situation, Task, Action, Result) for behavioral questions to keep your responses focused and impactful.
Prepare your own questions
Always have 2–3 thoughtful questions about the team’s tech stack or the company’s engineering culture. It shows genuine interest and engagement.
Review your resume
Be prepared to dive deep into any project listed on your resume. You should be able to explain the architecture and your specific contribution in detail.
Practice under pressure
Simulate interview conditions by solving problems within a time limit. This helps reduce anxiety during the actual interview.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
What are the key differences between various Java garbage collection algorithms?
What are the key differences between various Java garbage collection algorithms?
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?
Given a set of requirements, how do you determine the optimal data structure to use?
Given a set of requirements, how do you determine the optimal data structure to use?
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?
Can you refactor this piece of code to improve its time complexity?
Can you refactor this piece of code to improve its time complexity?
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?
Replace offset paging on the resource feed with keyset
resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.
Approach
- Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
- Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
- Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
- Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.
Follow-up
- The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
- Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?
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?
Can you walk me through the high-level architecture of your current project?
Can you walk me through the high-level architecture of your current project?
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 do you manage transaction management within a Spring Boot application?
How do you manage transaction management within a Spring Boot application?
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?
Explain the concept of distributed systems and how you handle consistency in such environments.
Explain the concept of distributed systems and how you handle consistency in such environments.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
How would you approach designing a scalable API for a high-traffic service?
How would you approach designing a scalable API for a high-traffic 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?
Every query on one table stalls for forty seconds mid-deploy
During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.
Approach
- Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
- Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
- Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
- Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.
Follow-up
- The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
- Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?
Built from the rounds and topics Truemeds candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Truemeds loop
- Write out the reported sequence: Recruiter Screen, Technical Rounds.
- 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 Coding and Problem Solving
- Spend the session on Coding and Problem Solving, which Truemeds candidates report being tested on.
- Write one worked example in Coding and Problem Solving and time yourself on it.
Deliverable: One timed worked example in Coding and Problem Solving.
03Work Java
- Spend the session on Java, which Truemeds candidates report being tested on.
- Write one worked example in Java and time yourself on it.
Deliverable: One timed worked example in Java.
04Work Python
- Spend the session on Python, which Truemeds candidates report being tested on.
- Write one worked example in Python and time yourself on it.
Deliverable: One timed worked example in Python.
05Answer out loud: Technical & Domain Expertise
- Answer aloud, timed: Can you walk me through the high-level architecture of your current project?
- Answer aloud, timed: How do you handle database indexing to optimize query performance?
Deliverable: Spoken answers to 2 reported Technical & Domain Expertise question(s), under time.
06Answer out loud: Coding & Problem Solving
- Answer aloud, timed: How would you approach designing a scalable API for a high-traffic service?
- Answer aloud, timed: Given a set of requirements, how do you determine the optimal data structure to use?
Deliverable: Spoken answers to 2 reported Coding & Problem Solving question(s), under time.
07Dry run for Truemeds
- 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.
How do you handle database indexing to optimize query performance?
How do you handle database indexing to optimize query performance?
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 edge cases when implementing a new feature?
How do you handle edge cases when implementing a new feature?
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 you had to debug a complex issue in a production environment.
Describe a time you had to debug a complex issue in a production 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?
- 01
How do you handle database indexing to optimize query performance?
- 02
How do you handle edge cases when implementing a new feature?
- 03
Describe a time you had to debug a complex issue in a production environment.
How long should I spend preparing for the technical rounds?
Dedicate at least 2–3 weeks to reviewing core concepts, specifically Java internals and system design. Consistent practice with coding problems on a platform of your choice will help you maintain speed and accuracy.
Truemeds Software Engineer candidate reports ↗Is there a specific focus for the coding rounds?
The coding rounds are typically standard DSA-based questions. Focus on writing clean, readable code and discussing the time and space complexity of your solution.
Truemeds Software Engineer candidate reports ↗What is the best way to handle a third-party interviewer?
Treat the third-party interviewer with the same professional focus as an internal one. If you encounter technical issues or have trouble understanding an accent, don't hesitate to ask for clarification or repeat the question to ensure you are aligned.
Truemeds Software Engineer candidate reports ↗What differentiates successful candidates?
Successful candidates are those who can explain the reasoning behind their technical choices. Don't just provide a solution; explain why that solution is the most efficient or scalable option for the given constraints.
Truemeds Software Engineer candidate reports ↗How many rounds is the Truemeds Software Engineer interview process?
Candidates report 2 stages: Recruiter Screen and Technical Rounds. The interview process section above breaks down what each stage covers.
Truemeds Software Engineer candidate reports ↗What topics come up in the Truemeds Software Engineer interview?
Truemeds Software Engineer interviews most often cover Coding and Problem Solving, Java, Python, DSA (Data Structures and Algorithms), and AWS Lambda, based on topics extracted from real candidate reports.
Truemeds Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
Official role evidence, timestamped platform data and clearly labeled preparation advice.
- 01Truemeds Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
candidate · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
platform · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
platform · Accessed 2026-09-22
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