Technical practice
How would you choose an LLM for a production application?
What to coverSuggested preparation: Explain how you would compare task performance, latency, cost, privacy constraints, and deployment options. Describe how you would validate the choice against the application's quality requirements rather than relying on a model's general reputation.
How would you incorporate generative AI into an existing application?
What to coverSuggested preparation: Walk through the application boundary, inputs and outputs, and how the model would connect to existing systems and workflows. Address failure handling and the trade-off between model flexibility and predictable behavior.
How would you evaluate and improve an existing AI model?
What to coverSuggested preparation: Define measures tied to the application's purpose, establish a baseline, and examine representative errors. Explain how you would test whether a change improves quality without degrading other important outcomes.
What would a production-ready AI application pipeline need to cover?
What to coverSuggested preparation: Compare cloud and on-premises deployment considerations for an AI application. Discuss testing, deployment, observability, and recovery as ways to support the production-quality standard stated in the posting.
How would you troubleshoot declining quality in a deployed AI application?
What to coverSuggested preparation: Explain how you would separate changes in inputs, model behavior, and application integration. Describe what evidence you would collect before choosing between a model change, a pipeline fix, or a workflow change.
How would you use TensorFlow or PyTorch to develop a deep learning model?
What to coverSuggested preparation: Outline the training and validation workflow, including data preparation, loss selection, and checks for overfitting. Relate framework choices to the model and deployment needs rather than claiming the role requires one particular framework.
Which NLP techniques would you consider for a language-based application?
What to coverSuggested preparation: Explain how text preparation, representation, and evaluation would depend on the task. Contrast a simpler NLP approach with an LLM-based approach where accuracy, complexity, or operating cost might affect the decision.
How would you design and deploy a conversational agent?
What to coverSuggested preparation: Cover conversation flow, handling unclear requests, and testing responses across realistic interactions. Explain how you would assess whether the agent works reliably after integration with the application.
When would cloud-based AI services be useful for this role?
What to coverSuggested preparation: Compare a managed service with a self-managed deployment in terms of integration effort, operational control, cost, and data constraints. Cloud-based AI services are listed as a good-to-have skill, not a required provider or product.
How might image processing fit into an AI solution?
What to coverSuggested preparation: The posting lists image processing as a possible area, so treat this as optional preparation. Explain how you would define the image task, select an appropriate approach, and evaluate output quality before integrating it into an application.
Behavioural practice
Tell me about a consequential technical decision you made for a team.
What to coverSuggested preparation: Use a real situation to explain the decision, alternatives considered, and how you involved the team. State your actions and the result, including what you learned if the outcome was mixed.
Describe a time you integrated a solution across different teams.
What to coverSuggested preparation: Give the situation and explain how you aligned requirements, interfaces, or workflows with stakeholders. Describe your actions and the resulting integration outcome.
Tell me about a problem you helped resolve across multiple teams.
What to coverSuggested preparation: Identify the situation, the teams affected, and how you distinguished the underlying issue from its symptoms. Explain your actions, coordination, and measurable or observable result.
Describe how you mentored a junior team member.
What to coverSuggested preparation: Give a specific situation and the skill or knowledge gap you addressed. Explain what you did, how you adjusted your support, and what changed as a result.
Tell me about a time you helped a team improve its performance.
What to coverSuggested preparation: Describe the situation and how you identified an obstacle to delivery or quality. Explain the actions you took with the team and the resulting change, without overstating your individual contribution.