Handshake, an early-career network connecting students and employers, successfully deployed and scaled over 15 large language model (LLM) use cases in six months by leveraging a strategic orchestration layer and Arize AX for observability and evaluations. The company created a microservice called LLM Orca to provide a centralized and efficient pathway for launching LLM-powered features, ensuring robustness amid rapid advancements in LLM research. This service integrates with tools like Arize AX and Datadog to trace and evaluate every call, allowing for cost breakdown, automated workflows, and prompt-engineering evaluations. Since implementing Orca, Handshake has launched various LLM-powered features such as AI-generated recruiter messages and job tagging, achieving a unified quality assurance process and faster iteration with minimized risks of LLM hallucinations. Handshake's approach demonstrates how a lightweight orchestration layer and comprehensive evaluation can empower product teams to quickly ship and validate valuable features without compromising reliability or accountability.