Responsibilities:
• Design multi-agent orchestration systems (LangGraph, LangChain, or equivalent)
• Build and optimize RAG pipelines (vector databases, embeddings, retrieval quality)
• Develop structured LLM outputs & advanced prompt engineering
• Create AI-driven features for sales workflows (CRM, pipelines, forecasting, lead scoring)
• Integrate AI into booking & reservation systems (availability, scheduling, workflows)
• Evaluate LLM system performance (accuracy, faithfulness, memory)
• Combine classical ML with LLM-based reasoning when needed
•
Qualifications:
• 5+ years of engineering experience
• Strong GenAI engineering experience (LangChain, LangGraph, or similar)
• Hands-on RAG experience (pgvector, FAISS, Pinecone, retrieval tuning)
• Production-level Python (FastAPI, asyncio, Pydantic)
• Experience with multi-agent systems
• Structured outputs (JSON schema / function calling)
• Strong understanding of sales domains (CRM, pipelines, forecasting, RevOps)
• Experience with booking & reservation systems (hospitality/travel platforms)
Nice to Have:
• Background in Machine Learning (classification, clustering, scikit-learn)
• Experience with LLM evaluation frameworks (Ragas or custom evaluations)
• Familiarity with CRM platforms (Salesforce, HubSpot)
• Exposure to PMS / booking platforms
• Knowledge of graph systems or knowledge graphs