65 Generative AI System Design Interview Questions

All 65 questions

How would you design a maintainable, evaluable LLM system?
Asked in 2 of 291 interviews · last asked Sep 9 · Design · Mid-level
Other ways it was asked
- “How would you build an evaluation framework for a production LLM system?”
How would you design a chatbot's architecture, including backend entities, chat flow, streaming, and context management?
Asked in 2 of 291 interviews · last asked Jul 28 · Design · Senior
Other ways it was asked
- “Can you describe the technical architecture of an AI chatbot and explain how you would design and implement it?”
- “How would you design the backend for a chatbot, including its core entities, chat flow, streaming, and context management?”
How would you debug a chatbot that is slow and sometimes gives incorrect answers about product specifications?
Asked once · last asked Jul 16 · Scenario · Mid-level
How would you design and implement an internal low-code/no-code generative AI application to accelerate functional scoping for projects?
Asked once · last asked Sep 20 · Design · Senior
If the application has direct database access, why use an LLM, and how would you design the solution?
Asked once · last asked Sep 25 · Design · Senior
Other ways it was asked
- “If we have direct database access, why use an LLM to query the database, and why make the design complicated?”
How should a company respond when its customer support AI gives a customer an incorrect answer?
Asked once · last asked Apr 20 · Scenario · Mid-level
Other ways it was asked
- “How should a company respond when Zendesk's AI gives a customer an incorrect answer?”
When you integrate an LLM into a CMS to generate on-brand SEO copy, what exact guardrails do you implement to prevent keyword stuffing and voice drift before anything is published?
Asked once · last asked May 28 · Scenario · Senior
Write a Python function that takes a PDF filename, extracts its contents, and summarizes them using an OpenAI model.
Asked once · last asked Jun 12 · Write code · Mid-level
What challenges arise when integrating AI with Playwright to create tests, how would you address them, and what safeguards would you use to limit errors and hallucinations?
Asked once · last asked Jun 18 · Behavioral · Senior
Other ways it was asked
- “What challenges have you encountered when integrating AI with Playwright to create tests, how did you address them, and what safeguards do you use to limit errors and hallucinations?”
How do you debug AI-generated results in API tests and applications?
Asked once · last asked Jun 18 · Scenario · Senior
If you were implementing a generative AI solution for personalized marketing content at scale, what key architectural components would you design, and how would you address data privacy, model bias, and content diversity?
Asked once · last asked Jul 16 · Design · Senior
How do you work with FastAPI and LangChain, and how are they interconnected?
Asked once · last asked Jul 16 · Concept · Mid-level
Which AI models support voice input and output for an automated phone-call system?
Asked once · last asked Jul 16 · Concept · Mid-level
Why might you choose Claude Sonnet over Claude Haiku for an application?
Asked once · last asked Jul 16 · Concept · Mid-level
How would you integrate an LLM API while accounting for errors, cost, latency, and moderation?
Asked once · last asked Jul 21 · Design · Senior
How would you integrate an LLM into an application and handle errors?
Asked once · last asked Jul 22 · Scenario · Mid-level
When you're building an AI feature that uses LLMs, how do you ensure that the requirements and acceptance criteria align closely with actual user needs?
Asked once · last asked Jul 23 · Scenario · Junior
How would you integrate an LLM into a chatbot?
Asked once · last asked Jul 25 · Scenario · Mid-level
Why might deterministic business rules belong in application code rather than an AI prompt?
Asked once · last asked Jul 26 · Concept · Senior
What could go wrong if you changed an AI prompt but not the worker code that enforces the same rule?
Asked once · last asked Jul 26 · Scenario · Senior
How would you advise a startup technical founder on selecting the right model for a chatbot use case?
Asked once · last asked Jul 27 · Scenario · Senior
What approaches would you take to optimize or improve the performance of a generic LLM that isn't performing well out of the box?
Asked once · last asked Jul 27 · Scenario · Senior
What are the considerations for using open-source local LLMs?
Asked once · last asked Jul 29 · Concept · Mid-level
How would you choose an LLM model family and tier for a use case when model costs differ significantly?
Asked once · last asked Aug 5 · Scenario · Senior
How are prompt engineering, RAG, spec-driven development, and agent orchestration used in AI applications?
Asked once · last asked Aug 5 · Concept · Mid-level
How can LLMs be used to solve technically challenging problems in software products?
Asked once · last asked Aug 7 · Scenario · Senior
An LLM application worked well in production yesterday, but its answers are poor today. How would you investigate the problem?
Asked once · last asked Aug 13 · Scenario · Senior
How would you automate an AI-powered process while managing token limits and Gemini API keys?
Asked once · last asked Aug 14 · Scenario · Mid-level
How would you compare training a custom LLM with using a multi-agent architecture, and when would you choose each?
Asked once · last asked Aug 18 · Concept · Mid-level
What do you look for when assessing Kubernetes or containers, and how would you approach assessing an AI or LLM-based application?
Asked once · last asked Aug 21 · Scenario · Senior
How would you integrate GenAI or LLM APIs into a Python application?
Asked once · last asked Aug 22 · Scenario · Mid-level
How would you manage model selection, cost, latency, hallucinations, and data privacy in a GenAI application?
Asked once · last asked Aug 22 · Scenario · Senior
When you build an LLM-based feature, what are the first three things you decide upfront—such as model choice, prompting approach, and RAG or tools—and why?
Asked once · last asked Aug 24 · Design · Senior
How can LLMs be used in medical applications, and how do they work?
Asked once · last asked Sep 4 · Concept · Mid-level
What considerations would justify choosing GPT-4.1 for a chatbot?
Asked once · last asked Sep 7 · Concept · Senior
How would you design a production LLM feature using AWS Bedrock?
Asked once · last asked Sep 9 · Design · Senior
What happens in a chatbot's request flow after an analyst submits a query?
Asked once · last asked Sep 10 · Design · Mid-level
How would you begin integrating an LLM into a live chat where latency and cost are critical?
Asked once · last asked Sep 18 · Design · Senior
How would you monitor LLM quality and system observability to detect when responses start to degrade?
Asked once · last asked Sep 18 · Scenario · Senior
How would you design a production AI chat application with React and ASP.NET Core to stream responses while controlling latency and cost?
Asked once · last asked Sep 18 · Design · Senior
Would you use large language models, small language models, or classical machine learning to build a B2B cross-sell and upsell recommendation model?
Asked once · last asked Sep 22 · Scenario · Senior
How would you assess product-market fit for a small language model feature before investing in model training and evaluation?
Asked once · last asked Sep 22 · Scenario · Senior
Describe a situation in which you would deploy an LLM within a company.
Asked once · last asked Sep 22 · Scenario · Mid-level
When would you run an LLM locally rather than use a third-party API?
Asked once · last asked Sep 23 · Scenario · Senior
A generative AI application is hallucinating and takes 10 seconds to return a prediction, but the business requires a response within 1 second. What would you do?
Asked once · last asked Sep 23 · Scenario · Senior
Tell about a time AI fell short in your work — something you tried to generate with an AI model that didn't work well.
Asked once · last asked Sep 25 · Behavioral
For an assistant that explains trends in farm benchmark data, how would you choose an initial use case and decide whether it is ready for a pilot?
Asked once · last asked Oct 1 · Scenario · Senior
If an AI assistant passes revised tests and enters a small internal pilot, what would you monitor, and what would make you pause or stop the pilot?
Asked once · last asked Oct 1 · Scenario · Senior
What legal and technical challenges do you see if a university wants to run an LLM endpoint on premise?
Asked once · last asked Oct 2 · Design · Senior
How would you design a text-to-SQL pipeline for live database analytics, such as finding total sales from Delhi in the last month?
Asked once · last asked Oct 7 · Design · Senior
What would you do if an AI tool gave a customer an incorrect answer?
Asked once · last asked Oct 8 · Scenario · Mid-level
When would you choose Azure OpenAI instead of Llama or another available model or API?
Asked once · last asked Oct 9 · Design · Mid-level
Other ways it was asked
- “Why did you choose Azure OpenAI instead of Llama or another available model or API?”
How do you use LLMs or other AI agents in game development workflows for code, content, and testing, and what are their biggest current capability gaps?
Asked once · last asked Oct 9 · Senior
How do you troubleshoot AI agent issues or hallucinations in a running application?
Asked once · last asked Oct 15 · Scenario · Mid-level
On local models in Ollama or LM Studio, how do you decide which model to run for a task, and what parameters do you typically tune, such as context length, temperature, or system prompt?
Asked once · last asked Oct 17 · Tooling · Senior
If an LLM translation fails on a category screen and the app falls back to the original English list, why might that be a good choice, what are its costs, and how would you detect failures in production?
Asked once · last asked Oct 19 · Scenario · Mid-level
How would you design an event-driven pipeline using Kafka and Claude to handle growth?
Asked once · last asked Oct 20 · Design · Senior
Design an AI-powered customer support chatbot for 10,000 concurrent users.
Asked once · last asked Oct 21 · Design · Senior
What language models would you consider for an AI system that makes insurance calls?
Asked once · last asked Jul 16 · Concept · Mid-level
Other ways it was asked
- “What challenges can arise when using language models in an AI system that makes insurance calls?”
Why would you use LangChain to build an AI application?
Asked once · last asked Apr 29 · Tooling · Mid-level
What are the three most common failure points in a chatbot that answers product questions?
Asked once · last asked Jul 16 · Concept · Mid-level
How would you build an LLM-powered chatbot using a Python backend?
Asked once · last asked Jul 16 · Design · Mid-level
Other ways it was asked
- “How did you build an LLM-powered chatbot using a Python backend?”
How would you select an LLM for a project?
Asked once · last asked Aug 3 · Scenario · Mid-level
Can you tell me a few use cases where LLMs are used?
Asked once · last asked Aug 7 · Concept · Junior
What are the usage limits of the free Gemini API tier?
Asked once · last asked Aug 25 · Concept · Junior

How this list is made

Every question here was asked by a real interviewer in a real job interview that a candidate ran MeetAssist in. After the call, the interviewer's questions are pulled from the transcript. Practice sessions, tests, exams and anything that was not a job interview are dropped.

Questions are rewritten so they make sense on their own: names of people, employers and clients are removed, and speech-to-text mistakes are fixed. Small talk, logistics and questions about one candidate's own résumé are left out. Rephrasings of the same question are merged, and the count is the number of different interviews it came up in.

The interviews come from candidates who use MeetAssist, so they lean towards software, data and AI roles: the shares describe these interviews, not every Generative AI and LLM interview. Answers to the most asked questions are written and checked by an editor; a "common mistake" is shown only when reviews of real answers in these interviews show it, with the count.

291 interviews, 178 candidates, Feb 2026 to Oct 2026. Updated every month with new interviews.

All 65 questions

How would you design a maintainable, evaluable LLM system?

How would you design a chatbot's architecture, including backend entities, chat flow, streaming, and context management?

How would you debug a chatbot that is slow and sometimes gives incorrect answers about product specifications?

How would you design and implement an internal low-code/no-code generative AI application to accelerate functional scoping for projects?

If the application has direct database access, why use an LLM, and how would you design the solution?

How should a company respond when its customer support AI gives a customer an incorrect answer?

When you integrate an LLM into a CMS to generate on-brand SEO copy, what exact guardrails do you implement to prevent keyword stuffing and voice drift before anything is published?

Write a Python function that takes a PDF filename, extracts its contents, and summarizes them using an OpenAI model.

What challenges arise when integrating AI with Playwright to create tests, how would you address them, and what safeguards would you use to limit errors and hallucinations?

How do you debug AI-generated results in API tests and applications?

If you were implementing a generative AI solution for personalized marketing content at scale, what key architectural components would you design, and how would you address data privacy, model bias, and content diversity?

How do you work with FastAPI and LangChain, and how are they interconnected?

Which AI models support voice input and output for an automated phone-call system?

Why might you choose Claude Sonnet over Claude Haiku for an application?

How would you integrate an LLM API while accounting for errors, cost, latency, and moderation?

How would you integrate an LLM into an application and handle errors?

When you're building an AI feature that uses LLMs, how do you ensure that the requirements and acceptance criteria align closely with actual user needs?

How would you integrate an LLM into a chatbot?

Why might deterministic business rules belong in application code rather than an AI prompt?

What could go wrong if you changed an AI prompt but not the worker code that enforces the same rule?

How would you advise a startup technical founder on selecting the right model for a chatbot use case?

What approaches would you take to optimize or improve the performance of a generic LLM that isn't performing well out of the box?

What are the considerations for using open-source local LLMs?

How would you choose an LLM model family and tier for a use case when model costs differ significantly?

How are prompt engineering, RAG, spec-driven development, and agent orchestration used in AI applications?

How can LLMs be used to solve technically challenging problems in software products?

An LLM application worked well in production yesterday, but its answers are poor today. How would you investigate the problem?

How would you automate an AI-powered process while managing token limits and Gemini API keys?

How would you compare training a custom LLM with using a multi-agent architecture, and when would you choose each?

What do you look for when assessing Kubernetes or containers, and how would you approach assessing an AI or LLM-based application?

How would you integrate GenAI or LLM APIs into a Python application?

How would you manage model selection, cost, latency, hallucinations, and data privacy in a GenAI application?

When you build an LLM-based feature, what are the first three things you decide upfront—such as model choice, prompting approach, and RAG or tools—and why?

How can LLMs be used in medical applications, and how do they work?

What considerations would justify choosing GPT-4.1 for a chatbot?

How would you design a production LLM feature using AWS Bedrock?

What happens in a chatbot's request flow after an analyst submits a query?

How would you begin integrating an LLM into a live chat where latency and cost are critical?

How would you monitor LLM quality and system observability to detect when responses start to degrade?

How would you design a production AI chat application with React and ASP.NET Core to stream responses while controlling latency and cost?

Would you use large language models, small language models, or classical machine learning to build a B2B cross-sell and upsell recommendation model?

How would you assess product-market fit for a small language model feature before investing in model training and evaluation?

Describe a situation in which you would deploy an LLM within a company.

When would you run an LLM locally rather than use a third-party API?

A generative AI application is hallucinating and takes 10 seconds to return a prediction, but the business requires a response within 1 second. What would you do?

Tell about a time AI fell short in your work — something you tried to generate with an AI model that didn't work well.

For an assistant that explains trends in farm benchmark data, how would you choose an initial use case and decide whether it is ready for a pilot?

If an AI assistant passes revised tests and enters a small internal pilot, what would you monitor, and what would make you pause or stop the pilot?

What legal and technical challenges do you see if a university wants to run an LLM endpoint on premise?

How would you design a text-to-SQL pipeline for live database analytics, such as finding total sales from Delhi in the last month?

What would you do if an AI tool gave a customer an incorrect answer?

When would you choose Azure OpenAI instead of Llama or another available model or API?

How do you use LLMs or other AI agents in game development workflows for code, content, and testing, and what are their biggest current capability gaps?

How do you troubleshoot AI agent issues or hallucinations in a running application?

On local models in Ollama or LM Studio, how do you decide which model to run for a task, and what parameters do you typically tune, such as context length, temperature, or system prompt?

If an LLM translation fails on a category screen and the app falls back to the original English list, why might that be a good choice, what are its costs, and how would you detect failures in production?

How would you design an event-driven pipeline using Kafka and Claude to handle growth?

Design an AI-powered customer support chatbot for 10,000 concurrent users.

What language models would you consider for an AI system that makes insurance calls?

Why would you use LangChain to build an AI application?

What are the three most common failure points in a chatbot that answers product questions?

How would you build an LLM-powered chatbot using a Python backend?

How would you select an LLM for a project?

Can you tell me a few use cases where LLMs are used?

What are the usage limits of the free Gemini API tier?

More Generative AI and LLM interview questions

How this list is made

Walk into your next interview ready.