Intercom AI Engineer Interview Questions
The questions to prepare for a Intercom AI Engineer interview. Questions from real interview reports rank first. Updated weekly.
Assign Intercom tasks to the least busy capacity-aware agent using a heap and deterministic tie-breaking.
Assign Intercom Inbox conversations to eligible teammates using weighted capacity, skill matching, and greedy utilization balancing.
Explain a practical approach to fine-tuning an LLM for a specific task, including data, evaluation, and hallucination risks.
Reduce hallucinations in a RAG system even when retrieval is already correct, using grounding, verification, and evaluation.
Design an LLM serving system that balances latency, cost, scalability, and safety for production traffic.
Tests understanding of embedding model trade-offs for accurate, fast retrieval in Intercom-style support search.
Assesses how you define metrics, instrumentation, and evaluation loops for production LLMs.
Discuss integrating a third party API into a pipeline and handling rate limits without duplicating or losing data.
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