Technical practice
How would you build a Python application that uses Claude or Azure OpenAI to solve a business task?
What to coverThe posting calls for Python-based, AI-powered applications using large language models or generative AI APIs. Suggested preparation: explain how you would structure API calls, handle failures, test outputs, and decide whether the application solves the stated task.
When would you use a multi-agent workflow rather than a simpler LLM application?
What to coverThe role includes autonomous and multi-agent workflows. Suggested preparation: describe how you would divide responsibilities, pass information between agents, and weigh added complexity against a simpler approach.
How would you connect Snowflake and Azure Databricks data to an AI workflow?
What to coverThe posting explicitly assigns building and maintaining pipelines that connect these platforms to AI and machine learning workflows. Suggested preparation: walk through data movement, transformation, and how you would keep the pipeline dependable.
How would you use SQL and dbt to provide trusted data for an agent?
What to coverStrong SQL skills and tools such as dbt are named in the posting, which emphasizes well-structured, trusted data. Suggested preparation: explain transformation logic, data checks, and how you would detect a change that makes model inputs unreliable.
An AI application's answers deteriorate after a data update. How would you investigate?
What to coverThe role connects data pipelines with models and agents, making this a relevant troubleshooting scenario rather than a stated incident. Suggested preparation: distinguish data-quality or pipeline changes from model behavior, then describe how you would isolate and verify a fix.
How would you approach deploying an AI application in the Azure ecosystem?
What to coverThe posting names Microsoft Azure and Azure AI Foundry and calls for deployed applications, but does not prescribe a deployment architecture. Suggested preparation: describe a plausible path from prototype to deployment, including testing, access considerations, and operational checks without assuming specific employer tooling.
How would you compare Claude, Azure OpenAI, and an emerging model for a proposed use case?
What to coverThe role involves these models and evaluating new AI tools for business value. Suggested preparation: explain how you would compare task quality, reliability, cost, and implementation effort against the same business objective.
What would you change before moving an AI prototype into production?
What to coverThe posting calls for rapid prototypes and production-ready solutions. Suggested preparation: discuss testing, failure handling, maintainability, and the trade-off between fast iteration and dependable operation.
How would you keep an autonomous workflow from taking an inappropriate action?
What to coverThe role includes autonomous workflows; the posting does not specify their permissions or controls. Suggested preparation: discuss limiting available actions, checking outputs, and deciding when a person should review a consequential step.
Behavioural practice
Tell me about a time you turned an ambiguous request into a working solution.
What to coverThe posting calls for translating ambiguous business needs into production-ready work. Suggested preparation: use a real situation, your actions to clarify the need and define success, and the resulting outcome.
Describe a time you coordinated across technical and business stakeholders.
What to coverThe role partners with data science, data engineering, IT, and business stakeholders. Suggested preparation: give a real situation, how you handled differing priorities or terminology, and the result of your coordination.
Tell me about a time you worked autonomously while a team's processes were still developing.
What to coverThe posting explicitly values autonomy in a newly established team with developing processes. Suggested preparation: describe the situation, how you set priorities or established a useful way of working, and what resulted.
Describe a time you evaluated a new technology before recommending whether to adopt it.
What to coverRapid evaluation of emerging AI tools, models, and frameworks is a stated responsibility. Suggested preparation: use a real example to explain the situation, your evaluation actions, and the outcome or decision.
Tell me about a time you balanced a fast prototype with production expectations.
What to coverThe role spans rapid prototyping and working, production-ready solutions. Suggested preparation: describe a real situation, the trade-offs and actions you took, and the result without presenting a hypothetical achievement as your own.