LLM Behavior & RAG Training Specialist (Voice Agent Integration)

Overview:Looking for an engineer skilled in LLM orchestration and adaptive conversational modeling. The role involves RAG-based contextual training, multi-turn dialogue behavior tuning, and prompt-state optimization within a live agent environment.⚙️ Core Competencies:Expertise in LangChain / LlamaIndex pipelines, vector DB structuring, and retrieval optimization.Command over token-level reasoning control, prompt engineering, and system message alignment for personality consistency.Practical experience with Vapi or equivalent voice orchestration frameworks.Strong understanding of embedding generation, document chunking, and semantic memory persistence.Ability to design emotion-conditioned dialogue layers and persona conditioning for human-like response flow.Familiar with API-based model adaptation, few-shot reinforcement loops, and real-time conversational evaluation.🧩 Preferred Stack:Python · OpenAI / Anthropic APIs · LangChain · Pinecone / Weaviate / Chroma · FastAPI · RAG architecture · Vapi / TTS-LLM integration · LLM fine-tuning💼 Ideal Background:AI Engineer or NLP Developer with proven experience in LLM customization, RAG retrieval logic, and behavioral response tuning for production-grade conversational systems.