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Sample Vetting Questions

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

Python

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

Next.js

7. Principal level, Mental Model. Explain what runs on the server, what runs in the browser and what is cached for one product page, and how you would prove it.

   A strong answer covers: Server and client components; Static, dynamic and streamed rendering; Data cache and full route cache; Inspecting the build output and headers.

8. Principal level, Accuracy. How do you protect server actions and route handlers from misuse?

   A strong answer covers: Authentication and authorization on every call; Input validation; CSRF and origin checks; Rate limits and error handling.

9. Principal level, Cognitive Load. Largest Contentful Paint is 4 seconds on mobile for a content page. What do you do and in what order?

   A strong answer covers: Field data first; Image priority and sizing; Server timing and caching; Fonts and third party scripts.

10. Principal level, Mental Model. How do you structure a large Next.js repository for several teams?

    A strong answer covers: Route and feature ownership; Shared packages; Import rules; Independent deploys or one app.

11. Staff level, Mental Model. What do you test with unit tests, component tests and end to end tests in a Next.js app?

    A strong answer covers: Server and client parts; Contracts with APIs; Flaky test cost; What to stop testing.

12. Principal level, Accuracy. An AI assistant produced a new page with data fetching and a form. What do you check first?

    A strong answer covers: Where each piece runs; Authorization on the server action; Caching and revalidation; Accessibility and tests.

Node.js

13. 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.

14. 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.

15. 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.

16. 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.

17. 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.

18. 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.

The five Axiom Cortex axes, with one example each

• Procedural Knowledge. Walk me through profiling a Python endpoint that is slow only in production. Looks for: Order of steps; What each step proves; What you do if the profile is flat.
• Mental Model. What is the difference between a server component and a client component, and what crosses the boundary? Looks for: Where code runs; What can be passed; Cost to the browser.
• Accuracy. What does a Promise.all do when one promise rejects, and what happens to the others? Looks for: Correct behavior; What it does not cancel; Says when it is unsure.
• Clarity. Explain to a finance partner why the nightly report was late twice this week. Looks for: One cause named; One decision for the listener; Plain words.
• Cognitive Load. A deploy just went out, error rates are up for some regions only and the cache shows mixed versions. 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