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Design an LLM inference platform (vLLM-as-a-service) serving many models and teams.

Limited GPUs, dozens of models, and every team demanding low latency for little money. The signal is whether you can shape that into a single governed serving fleet: continuous batching, KV cache, per-tenant quotas, and cost you can genuinely attribute.

Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.

Limited GPUs, dozens of models, and every team demanding low latency for little money. The signal is whether you can shape that into a single governed serving fleet: continuous batching, KV cache, per-tenant quotas, and cost you can genuinely attribute.

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