Technical practice
How would you build a product testing strategy for an AI application?
What to coverThe posting calls for product testing strategy and automation testing of AI products. Suggested preparation: explain how you would identify critical user flows, prioritize risks, and decide what to automate versus evaluate manually.
How would you test an AI product’s API?
What to coverAPI testing is an explicit responsibility. Suggested preparation: cover request and response validation, error handling, repeatable test data, and how you would investigate a failing test.
How would you structure BDD automation using Python, Behave and Git?
What to coverThe posting names BDD, Python, Behave, automation frameworks and Git. Suggested preparation: describe readable scenarios, reusable steps, maintainable test code and version control practices.
How would you evaluate LLM outputs for accuracy, relevance and context?
What to coverThose three qualities are explicitly named in the posting. Suggested preparation: explain how you would define evaluation criteria, assemble representative cases and handle outputs on which reviewers disagree.
How would you report evaluation results and support continuous validation?
What to coverThe role includes evaluation reporting, communication, feedback mechanisms and continuous validation. Suggested preparation: describe how you would make findings actionable, track recurring failures and check whether changes improve results.
How would you test bias, safety and fallback responses?
What to coverThe posting calls for testing bias, safety, non-subjective response handling and fallback behaviour. Suggested preparation: explain how you would select cases, assess responses against defined expectations and record ambiguous outcomes.
How would you probe harmful prompts and other edge cases?
What to coverHandling harmful prompts and edge cases is explicitly listed. Suggested preparation: discuss systematic case selection, safe test execution and how you would distinguish an isolated failure from a broader pattern.
How would you assess response-time performance under load?
What to coverThe posting specifies basic load testing, p50 and p95 measures, and response-time SLAs. Suggested preparation: explain what each percentile reveals, how you would compare results with an SLA and what you would investigate after a regression.
How would you integrate AI quality checks into CI/CD?
What to coverCI/CD integration is a responsibility; cloud-based pipelines are listed as nice to have. Suggested preparation: distinguish fast, repeatable checks from more variable LLM evaluations, and explain how you would make failures useful to developers.
How would you make pre-production test results traceable and auditable?
What to coverThe posting names data storage, traceability, auditability and consideration of applicable legal frameworks before production. Suggested preparation: explain what test inputs, outputs, versions and decisions you would retain, while noting that legal checks depend on the product and jurisdiction.
Behavioural practice
Tell me about a time you worked with data scientists or ML engineers to resolve a quality issue.
What to coverClose collaboration with those roles is listed as nice to have. Suggested preparation: give a real situation, the actions you took to align on evidence or evaluation criteria, and the result.
Tell me about a time you communicated a difficult test finding.
What to coverReporting and communicating evaluation results are part of the role. Suggested preparation: describe the situation, how you presented the evidence and recommended action, and what happened next.
Tell me about a time you raised a safety or bias concern before release.
What to coverThe posting calls for bias and safety testing before production. Suggested preparation: use a real example to explain the risk you found, how you escalated or investigated it, and the resulting decision without claiming a particular company process.
Tell me about a time feedback changed your testing approach.
What to coverFeedback mechanisms and continuous validation are stated responsibilities. Suggested preparation: describe the original approach, the feedback and action you took, and the measurable or observable result.
Tell me about a time you had to prioritize testing across competing risks.
What to coverThe role calls for a product testing strategy spanning automation, LLM evaluation and performance. Suggested preparation: explain the situation, how you chose what to test first, and the outcome or trade-off you identified.