AI-Powered Customer Conversation Platform Project Type: Multi-Tenant SaaS Platform Overview Building an AI-native conversation orchestration platform that helps businesses manage and automate customer conversations across WhatsApp and social media channels. The platform uses AI to provide intelligent next-best-action recommendations and tracks conversation outcomes. Tech Stack Required Backend: Python 3.13 or 3.14 + (FastAPI framework) PostgreSQL 15+ with SQLAlchemy ORM Redis for caching and job queues Multi-LLM integration (OpenAI, Anthropic, Groq) RESTful API design with OpenAPI/Swagger documentation Vector Database (Pinecone, Qdrant) Additional Technologies: React 18 + TypeScript frontend WhatsApp Cloud API integration (direct and via Solution Partners) Google Cloud Translation API JWT authentication and encryption Alembic for database migrations Key Requirements Multi-tenant architecture with row-level security Adapter pattern for external service integrations (LLM providers, messaging platforms) Event-driven architecture (Redis Streams) Webhook handling for real-time messaging RESTful APIs for workflow engine and AI orchestration Comprehensive testing (pytest) Clean code following Python best practices (Ruff linting) Deliverables Fully functional backend with API documentation Database schema and migrations Integration with WhatsApp Business API AI orchestration engine with multi-LLM support Multi-language translation service Comprehensive test coverage Deployment-ready codebase Ideal Candidate 3+ years Full Stack development experience including Python Strong FastAPI and PostgreSQL expertise Experience with multi-tenant SaaS applications Familiar with AI/LLM integrations Understanding of adapter/interface design patterns Experience with webhook handling and async processing Strong documentation and testing practices NDA + IP agreement Required | Milestone-based payments | Detailed architecture documentation provided