[MISSION] RAG system for an endangered spoken language — 10 weeks — full IP transfer

A client is seeking an experienced NLP/LLM engineer to build the first RAG-based localization engine for a low-resource South American language within 10 weeks, with full IP transfer and a budget of €5,000–€10,000.

Hi, I’m looking for an experienced NLP/LLM engineer for a serious, well-scoped project: building the first RAG-based localization engine for a low-resource language spoken in South America. The project is built on a proprietary corpus pedagogical content, dictionary, proverbs, orthographic rules developed over 4 years. Architecture, endpoints, quality criteria and deliverables are fully specified in a detailed technical brief available under NDA . Technical scope MVP — 10 weeks - RAG pipeline on low-resource language corpus LangChain or LlamaIndex - Multilingual embedding model multilingual-e5 or equivalent - Vector DB: Pinecone, Weaviate or Supabase pgvector — latency < 500ms - Modular prompt layer — 6 use-case templates translate, educate, dub, subtitle, localize, campaign - Multi-tenant B2B SaaS infrastructure — strict data isolation, JWT auth, configurable quotas - REST API + Swagger documentation - Admin interface for glossary management no-dev updates - Offline SQLite bundle for React Native mobile app Profile required - Proven RAG experience on low-resource or multilingual corpora - Multi-tenant SaaS architecture references - Modular prompt engineering in production Anthropic or OpenAI API - Full IP transfer to client — non-negotiable - NDA before corpus access - Budget: 5,000–10,000€ depending on experience - Start: within 2–3 weeks If this matches your profile, please reply with concrete references on RAG low-resource languages, multi-tenant SaaS architecture, and modular prompt engineering in production