Hire Nearshore Backend Developers in Argentina

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Sample Vetting Questions

Example questions at senior and principal level for Backend Developer, with what a strong answer covers. They show the depth TeamStation AI tests. They are not a real candidate interview.

Node.js

1. Principal level, Mental Model. An API answers fast on average but stalls for 800 ms every few minutes. How do you tell a blocked event loop from a slow dependency?

   A strong answer covers: Event loop delay measurement; CPU profile of the process; Separating synchronous work from waiting on I/O; Garbage collection pauses as a third cause.

2. Principal level, Mental Model. A downstream service starts timing out and your Node service falls over. Walk through what happens and how you stop it spreading.

   A strong answer covers: Timeouts on every call; Retries with a budget and jitter; Circuit breaking and bulkheads; Queue growth and memory.

3. Principal level, Cognitive Load. A job queue worker processes some jobs twice. List the causes and the design that makes duplicates harmless.

   A strong answer covers: At least once delivery; Visibility timeouts and slow jobs; Idempotent handlers; Dead letter handling.

4. Principal level, Accuracy. A critical vulnerability lands in a package three levels down your dependency tree. What do you do in the first hour?

   A strong answer covers: Is the code path reachable; Lockfile and tree inspection; Patch, override or mitigate; Telling the right people.

5. Principal level, Cognitive Load. CPU is flat, but p99 latency doubled after a deploy three hours ago. Give your first five actions.

   A strong answer covers: Compare versions; Event loop delay and dependency latency; Roll back or hold and why; Say what you know and do not know.

6. Principal level, Accuracy. An AI assistant wrote a new service in 400 lines. What do you check before you read it?

   A strong answer covers: Tests and what they prove; Dependencies it added; Error paths and timeouts; Behavior against the requirement.

Python

7. Principal level, Mental Model. A CPU bound Python service does not get faster when you add threads. Why, and what are your real options?

   A strong answer covers: The global interpreter lock and what it limits; Processes, native extensions or another service; I/O bound work being different; Newer free threaded builds and their trade offs.

8. Principal level, Mental Model. How do you introduce type checking into a 400,000 line untyped codebase without stopping delivery?

   A strong answer covers: Start at boundaries and new code; A gradual strictness ratchet in CI; Public interfaces first; What types will not catch.

9. Principal level, Cognitive Load. A nightly pipeline now takes 9 hours and used to take 2. How do you find the cause and make it safe to rerun?

   A strong answer covers: Stage timings and data volume growth; Skew and large joins; Idempotent writes; Checkpoints and partial reruns.

10. Principal level, Cognitive Load. A Django or FastAPI service has an N+1 query problem in one endpoint and the team added caching instead. What do you say?

    A strong answer covers: Fix the query first; Caching hides but does not remove cost; Invalidation cost; A test that guards the query count.

11. Principal level, Accuracy. Coverage is 92 percent and a serious bug still shipped. What does that show, and what do you add?

    A strong answer covers: Coverage measures lines run, not behavior; Property based or mutation testing; Tests at the boundaries; Production signals.

12. Principal level, Accuracy. An AI assistant wrote a data processing script that runs fine on a sample. What do you check before it touches production data?

    A strong answer covers: Edge cases in the data; Memory and runtime at full size; Idempotency and rollback; Who can see the output.

Java

13. Principal level, Mental Model. A service has a p99 latency spike every few minutes while average CPU stays flat. How do you tell a garbage collection pause from JIT recompilation, a safepoint delay or a noisy neighbor, and what do you capture before you touch any flag?

    A strong answer covers: GC logs, JFR and a profiler before any tuning; Allocation rate and humongous objects; Safepoint time versus pause time; Container CPU throttling as a separate cause.

14. Principal level, Mental Model. Describe a race condition that passed code review and testing. How did the Java Memory Model allow it, and what did the fix change?

    A strong answer covers: Visibility versus atomicity; Happens-before edges; Why a volatile flag fixes one problem and not the other; How to test it, for example with a concurrency stress tool.

15. Staff level, Procedural Knowledge. A JPA endpoint went from 40 ms to 4 s after a schema change. Walk through your diagnosis, including what you look at before you read the code.

    A strong answer covers: SQL actually sent, and how many statements; Execution plans and changed indexes; Fetch strategy and lazy loading inside serializers; Connection pool wait time.

16. Staff level, Procedural Knowledge. A monolith has 600 Spring beans and a 14 minute startup. What do you measure first, and what would you refuse to change?

    A strong answer covers: Startup tracing before any guess; Component scanning and eager initialization; Class data sharing and ahead of time options with their limits; Behavior you will not trade for speed.

17. Principal level, Cognitive Load. Heap climbs, the service restarts every 20 minutes, and a deploy went out 3 hours ago. Give your first five actions and one thing you decline to do.

    A strong answer covers: Roll back or hold, and why; Capture a heap dump or flight recording before the next restart; Limit the blast radius; Say what you know and do not know to the people waiting.

18. Staff level, Clarity. Explain a garbage collection tradeoff to a CFO who is asking why cloud spend rose 30 percent.

    A strong answer covers: Plain words and one number; Cost of lower pauses versus cost of more memory; A choice the CFO can make; No jargon the CFO has to ask about.

The five Axiom Cortex axes, with one example each

• Procedural Knowledge. Walk me through taking a heap snapshot from a Node process that keeps growing. Looks for: Order of steps; What each step proves; What you do if the first snapshot looks normal.
• Mental Model. Why does adding threads not speed up a CPU bound Python function? Looks for: The lock around the interpreter; CPU work versus waiting; Options that do help.
• Accuracy. What does the JVM size from a container CPU limit, and what does it not? Looks for: Correct limits; No invented numbers; Says when it is not sure.
• Clarity. Explain to a support lead why users saw errors for two minutes during a deploy. Looks for: One cause named; One decision for the listener; Plain words.
• Cognitive Load. A pipeline failed halfway, an executive is waiting on the report, and two upstream teams blame each other. What do you do first, second and third? Looks for: A clear order; Facts kept apart from guesses; Stays correct as facts change.

Questions answered on this route