AI Consultant with RAG experience

We are looking for a senior AI consultant with deep experience in Retrieval Augmented Generation (RAG) systems to advise on architecture, backend setup, and implementation strategies. This is a consultation role focused on design, planning, and architecture implementation guidance. Scope of Consultation & Deliverables: • Design and validate RAG system architecture, including backend services, APIs, and integration points • Advise on document ingestion pipelines, chunking strategies, and embedding approaches • Recommend vector database selection and implementation best practices for performance, scalability, and reliability • Guide on LLM selection, prompting strategy, and context management • Provide strategies to reduce hallucinations and improve answer reliability • Suggest backend patterns for orchestration, caching, scaling, logging, and monitoring • Recommend deployment, security, and data privacy best practices for production systems • Advise on cost, latency, and scalability optimizations • Review evaluation metrics for RAG quality and accuracy Deliverables: • Complete system architecture diagrams and documentation • Backend setup guidance with production-ready patterns • Ready-to-work boilerplate for RAG pipeline implementation Ideal Consultant Profile: • Strong background in Python-based AI systems and backend architecture • Proven experience designing and architecting RAG pipelines in production • Hands-on experience with LangChain, LlamaIndex, or custom RAG frameworks • Deep understanding of embeddings, vector search, retrieval strategies, and backend integrations • Experience consulting on real-world AI systems with actionable implementation guidance • Able to communicate clearly and provide concrete recommendations for architecture, backend setup, and boilerplate Engagement Details: • Consultation via calls, written feedback, architecture review sessions, and implementation guidance • Short-term engagement with potential follow-up sessions • Flexible hours Budget: Open to hourly or fixed consultation packages How to Apply: In your proposal, briefly explain: • One RAG system you have consulted on or architected • Key trade-offs you helped a team decide on • Your approach for backend architecture, RAG reliability, and boilerplate setup Those with new profiles looking to get some traction on the platform are encouraged to apply Apply tot his job