FDE interviews are unusual: they test whether you can be a great engineer and a great customer partner at the same time. Expect 4–6 rounds spanning technical depth, system design, LLM integration, debugging, and a customer simulation. Here's what each round looks like and how to answer.
Round 1: Technical screening
These confirm you can actually build. Expect practical coding (not always LeetCode-hard) and questions about your real projects.
Example: "Walk me through a system you built and deployed to production." How to answer: pick a project you owned end to end. Cover the problem, your architecture choices and why, what broke, and how you fixed it. Interviewers care more about your decision-making and ownership than the tech stack.
Example: "Build an endpoint that integrates an LLM to answer questions over a set of documents." How to answer: talk through retrieval (chunking, embeddings, vector search), the prompt, handling token limits, caching, and failure modes. Narrate tradeoffs out loud.
Round 2: System design
FDEs design real customer deployments, so this round is concrete, not abstract whiteboarding.
Example: "Design a system that deploys our AI product for an enterprise customer with strict security requirements." How to answer: clarify constraints first (data residency, on-prem vs cloud, compliance). Then cover ingestion, the model layer, secrets and access control, monitoring, and rollback. Explicitly ask "what are this customer's constraints?" — that question alone signals FDE thinking.
Example: "We're rolling this out to 50 customers. What breaks first and how do you monitor it?" How to answer: name concrete failure modes (rate limits, latency under load, cost blowups, a customer's data quirks) and the metrics/alerts you'd set. Show you think about scale and operations, not just the happy path.
Round 3: LLM / integration depth
Example: "This LLM feature is too slow and too expensive for the customer. What do you do?" How to answer: walk the levers — smaller/cheaper models for sub-tasks, caching, prompt trimming, batching, streaming for perceived latency, and measuring before optimizing. Mention you'd quantify cost-per-request first.
Example: "When would you fine-tune vs. use RAG vs. just prompt?" How to answer: default to prompting, reach for RAG when the model needs current/proprietary knowledge, and fine-tune only when you need consistent format/behavior at scale and have good data. Show you reach for the simplest thing that works.
Round 4: Debugging
Half an FDE's job is debugging customer production issues, so expect a live exercise.
Example: "The customer's integration suddenly returns empty results. What do you check first?" How to answer: be systematic — reproduce, check recent changes, read logs and error messages, isolate the layer (their data? the API? auth? a rate limit?), form a hypothesis, test it. Resist randomly changing things; narrate a methodology.
Round 5: Customer simulation (the differentiator)
This is where most engineers stumble. An interviewer role-plays a stressed or unhappy customer.
Example: "I'm the customer. Your implementation is two weeks late and my CEO is asking why we hired you." How to answer: don't get defensive and don't over-promise. Acknowledge the impact, give an honest status and a concrete plan with dates, and tell them what you need from them. Calm ownership beats a perfect technical answer here.
Example: "The customer insists on an approach you think is wrong. What do you do?" How to answer: understand why they want it, explain your concern in their terms (risk to their outcome), offer a recommendation, and — if they still disagree — disagree and commit while documenting the decision. Show judgment and respect, not stubbornness.
What gets you the offer
- You explain your reasoning out loud and ask clarifying questions before diving in
- You show genuine end-to-end ownership in your stories
- You stay calm and honest in the customer simulation
- You debug systematically instead of guessing
What gets you rejected
- Blaming customers or saying "that's not my job"
- Over-promising to avoid a hard conversation
- Jumping to code without clarifying the problem
- Never having shipped anything end to end
How to prepare
Build and deploy one real LLM application (it gives you stories for every round), practice explaining it to a non-technical friend, and rehearse the customer simulation out loud — it's the round people most underestimate. For the fundamentals behind these questions, see our guides on the skills that get you hired and how to become an FDE.