AI Backend Engineer for Multi-Tenant SaaS with Python, LLM, and RAG expertise

We’re looking for an experienced AI Backend Engineer to help us build and improve a multi-tenant SaaS platform powered by Python, LLMs, and RAG. The ideal candidate should be comfortable designing scalable backend systems, building LLM-powered features, implementing RAG pipelines, and working with databases and APIs in a multi-tenant environment. You’ll be responsible for developing reliable backend services, integrating AI capabilities, managing tenant-specific data and access, and building the infrastructure required to support secure and scalable AI-powered SaaS applications. What You’ll Be Doing --------------------------- Design and develop scalable backend services using Python Build and maintain multi-tenant SaaS architecture Develop LLM-powered features using OpenAI, Claude, or similar APIs Build and optimize RAG pipelines for document and knowledge-based AI applications Implement document ingestion, chunking, embeddings, retrieval, and generation workflows Work with PostgreSQL, vector databases, and other data stores Develop and integrate REST APIs and third-party services Implement tenant-level data isolation, authentication, authorization, and access control Optimize AI workflows for performance, reliability, and cost What We’re Looking For ------------------------------ Proven experience developing backend applications with Python Strong understanding of multi-tenant SaaS architecture Hands-on experience with LLM APIs and AI application development Practical experience building RAG-based applications Good understanding of embeddings, vector search, semantic retrieval, and prompt engineering Experience with PostgreSQL and vector databases Good understanding of REST APIs, JSON, authentication, and third-party integrations Ability to design clean, scalable, and maintainable backend systems Strong debugging and problem-solving skills Experience with FastAPI, Django, or similar Python frameworks is a plus Experience with AWS, Docker, Redis, Celery, or background job systems is a plus To Apply Please share a few examples of Python backend systems, multi-tenant SaaS platforms, LLM applications, or RAG-based systems you have built. Briefly explain your role, the architecture used, and which technologies you worked with.