Technical practice
How would you use Python to prototype a small LLM application?
What to coverThe posting prefers basic Python knowledge and describes building AI applications. Suggested answer: outline how you would separate input handling, model calls and output checks, and explain how you would test each part.
How do LLMs differ from a conventional machine-learning model used for a specific prediction task?
What to coverThe posting lists machine-learning fundamentals, deep learning, NLP and LLMs as useful background. Suggested answer: explain the difference in purpose and outputs at a basic level, including why generated text needs to be checked for relevance and accuracy.
What are the main stages of a retrieval-augmented generation pipeline?
What to coverBuilding and improving RAG pipelines is a stated responsibility. Suggested answer: trace a question through document preparation, retrieval, context assembly and generation, then explain how you would check whether the answer is supported by the retrieved material.
What would you investigate if a RAG application retrieved irrelevant material?
What to coverThe posting mentions RAG improvement and basic familiarity with vector databases as a plus. Suggested answer: distinguish retrieval problems from generation problems, and discuss checking the source documents, how they are split, and whether the retrieved passages match the question.
How would you assess whether a prompt change improves an AI response?
What to coverPrompt engineering to improve responses is part of the advertised work. Suggested answer: compare outputs on the same representative inputs using clear criteria, such as task completion and factual support, rather than relying on one appealing example.
When would you use an AI agent rather than a single model call?
What to coverThe posting describes designing agents for complex tasks and exploring multi-agent systems. Suggested answer: explain when a task may need several decisions or steps, and weigh that flexibility against added complexity and harder-to-debug behavior.
How would you outline an AI-driven workflow that automates a repeated task?
What to coverAI automation and workflow orchestration are named areas of work. Suggested answer: identify the task’s inputs, steps, outputs and points where a person should review the result; explain how you would notice and handle a failed step.
What would you check when integrating an LLM through an API?
What to coverThe posting calls for model integration through APIs and lists REST and LLM APIs as useful familiarity. Suggested answer: describe request and response handling, error cases and a simple integration test, without assuming the team uses a particular provider.
How would you debug and improve an AI application that gives inconsistent results?
What to coverTesting, debugging and optimizing AI applications are stated responsibilities. Suggested answer: reproduce the issue with recorded inputs, isolate the relevant component, and compare results before and after a change using consistent test cases.
How would you evaluate whether an LLM framework is useful for a small project?
What to coverThe posting mentions modern LLM frameworks, names LangChain, LangGraph and LlamaIndex as preferred but not mandatory, and asks interns to research AI developments. Suggested answer: compare a framework with a simpler implementation on fit, ease of testing and maintenance, then describe how you would document the choice.
Behavioural practice
Tell me about a time you learned an unfamiliar technical concept to complete a task.
What to coverContinuous learning and experimentation are emphasized in the posting. Suggested answer: use a real course, personal or work example and explain the situation, what you did to learn and apply the concept, and the result.
Describe a time you worked with others to solve a technical problem.
What to coverThe role involves cross-functional collaboration and sharing ideas. Suggested answer: describe the situation, your specific contribution and how you communicated or resolved differing views, then state the outcome.
Tell me about a time you found and fixed a problem in something you built.
What to coverThe posting calls for testing, debugging, problem-solving and ownership. Suggested answer: identify the original problem, the steps you took to investigate it, and the result, including how you verified the fix.
Describe a time you explained or documented technical work for someone else.
What to coverDocumenting work, communicating results and sharing knowledge are part of the stated role. Suggested answer: explain the audience and situation, how you made the information usable, and what happened afterward.
Tell me about a time an experiment or initial approach did not work.
What to coverThe posting emphasizes practical experimentation and continuous improvement. Suggested answer: describe the goal, what evidence showed the approach was not working, what you changed and the result; a personal or academic project is suitable if that is your real example.