Senior Full-Stack & AI Engineer (Django, React, GenAI)

We are looking for a Senior Full-Stack Engineer with deep expertise in Django, React, and modern Generative AI architectures to help expand and enhance our existing platform. The ideal candidate brings 6+ years of hands-on experience building scalable web applications, paired with proven experience integrating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and vector stores into production environments. In this role, you will take ownership of full-stack feature delivery, optimize complex backend logic, and architect end-to-end AI workflows to drive high-impact features for our users. Key Responsibilities Full-Stack Development: Extend and maintain our existing application using Django (Python) on the backend and React on the frontend. AI Integration & Pipeline Design: Design, deploy, and optimize production-grade RAG pipelines, LLM prompts, and agentic workflows using LangChain. Vector Search & Data Management: Implement and manage vector databases (e.g., Pinecone, Weaviate, Qdrant, or Pgvector) for efficient context retrieval and similarity search. Cloud & Infrastructure: Containerize applications using Docker and manage deployment pipelines on AWS (EC2, ECS/EKS, S3, Lambda). Performance & Architecture: Ensure high code quality, system efficiency, robust API security, and seamless data flow between legacy components and AI services. Required Qualifications & Skills Core Engineering Experience 6+ years of professional experience in software engineering. Strong proficiency in Python and Django (REST Framework, ORM optimization, database indexing). Strong proficiency in React (State management, Hooks, modern UI components, async data fetching). Generative AI & Machine Learning Stack Hands-on experience integrating LLMs (OpenAI APIs, Anthropic, open-source models via Hugging Face/vLLM). Practical experience building RAG architectures and handling document ingestion/chunking strategies. Mastery of LangChain (or LlamaIndex) for building LLM-driven applications and chains. Experience working with Vector Databases (Pinecone, Weaviate, Qdrant, ChromaDB, or Pgvector). DevOps & Deployment Experience with Docker for local development and containerized production workflows. Cloud deployment expertise on AWS (ECS, EKS, EC2, CloudFront, RDS, or Serverless framework). Familiarity with CI/CD pipelines, automated testing, and web security best practices. Preferred Qualifications Experience deploying LLMs or AI middleware to high-traffic production environments. Knowledge of asynchronous task queues (Celery, Redis) and WebSocket implementations in Django/React. Experience with TypeScript and modern frontend build tools (Vite, Webpack).