Build an OWL Ontology for a Pharma R&D Knowledge Base

Between a customer who wants "AI" and a cloud bill that won't bankrupt them stands the solutions architect. This is the person sketching whiteboards: which model, which vector store, which guardrails, which inference budget. The role is partly engineering and partly translation — taking what a business is trying to achieve and shaping it into a reference architecture that other teams can build against. Strong architects know that token economics matter as much as accuracy, and that a slow answer is often a wrong answer. Students grow into this path by getting their hands dirty with cloud services like Vertex AI or Bedrock and learning to defend architectural choices with numbers, not vibes.

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