Senior AI Engineer for Agentic Systems

Must-haves 5+ years backend Python Has shipped at least one production LLM agent (tool-using, not a chat wrapper). They should be able to describe what broke and how they measured quality. Hands-on with Claude SDK / OpenAI Assistants / LangGraph (Claude SDK preferred — your stack) RAG in production: chunking strategy choices, hybrid search, retrieval evaluation Vector DB experience: Qdrant, pgvector, or Pinecone Treats prompt engineering as an engineering discipline — has eval suites, not just "vibes-based" iteration Has built at least one system with feedback loops (not static RAG that's frozen on day one) Strong nice-to-haves Frappe / ERPNext experience (willingness to learn it is fine — it's quirky but documented) Insurance, fintech, or another regulated-data domain Telegram Bot API Document AI: Google Vision, Textract, or layout-aware OCR Eval frameworks: Braintrust, LangSmith, or has rolled their own