Full-Stack Developer (Python/React/AI)

We are an innovative company developing a cutting-edge Legal Document Automation platform powered by AI/LLM. Our mission is to streamline legal workflows through smart technology. We are looking for a Senior Full-Stack Developer with strong expertise in AI/LLM and SaaS development to take the lead in building our platform from the ground up to a ready-to-launch MVP.

Must-Have Qualifications:
-5–7 years of proven experience in software development.
-Hands-on experience (1–2 years) with AI/LLM projects.
-Strong skills in both Backend and Frontend Development.
-Backend: Python (FastAPI/Django), Node.js (Express/NestJS), RESTful APIs, GraphQL, WebSocket, PostgreSQL, Redis, Vector Databases.
-Frontend: React + TypeScript, Redux/Zustand/Recoil, UI Libraries (Ant Design / Material-UI), real-time development ( ---------- ).
-Experience with file processing (PDF parsing, OCR, document analysis).
-Cloud & DevOps knowledge: AWS/GCP, Docker, CI/CD, monitoring tools, and security best practices.
-Experience working with AI APIs (OpenAI, Anthropic Claude), Prompt Engineering, RAG systems, embeddings, and similarity search.

Key Responsibilities
-Lead the development of the Legal Document Automation SaaS platform from scratch to MVP.
-Design and implement secure, scalable, and high-performance backend and frontend systems.
-Develop AI/LLM features, including prompt optimization, RAG systems, and smart document processing.
-Build advanced user interfaces such as chat systems, document upload, and processing workflows.
-Manage integrations with cloud services (AWS/GCP) and implement CI/CD pipelines.
-Collaborate closely with the founder and product team to deliver solutions aligned with business goals.
-Ensure best practices in data security, application architecture, and performance optimization.

Nice to Have (Plus to Have)
-Experience with Legal Tech or document automation systems.
-Familiarity with OCR tools (Tesseract, Google Document AI).
-Workflow automation and understanding of document lifecycle.
-Advanced AI/ML experience with LangChain, LlamaIndex, or fine-tuning domain-specific models.
-Knowledge of microservices, message queues (RabbitMQ, Kafka), database optimization, load balancing, and caching strategies.