




Job Summary: The Mid-level Fullstack Developer will be responsible for building and evolving solutions based on LLMs, RAG, and intelligent automation for a strategic AI and Chatbot project. Key Highlights: 1. Participation in a strategic AI and Chatbot project 2. End-to-end development with generative AI 3. Focus on LLMs, RAG, and intelligent automation **Description** The **Mid-level Fullstack Developer** will join a dedicated squad for HSystem's strategic AI and Chatbot project, working on the construction, evolution, and orchestration of solutions based on LLMs, RAG, and intelligent automation. You will be responsible for end-to-end feature development, integrating backend, integrations, and advanced generative AI techniques. Your contribution will be essential across all stages of the process, ensuring quality, efficiency, and continuous evolution of HSystem's solutions. **Responsibilities and Duties** Develop and maintain robust, scalable applications using Python (with Lambdas) and .NET Core 8\. Design and implement RAG (Retrieval\-Augmented Generation) pipelines integrated with the chatbot and HSystem's systems. Create, optimize, and evaluate advanced prompts, including persona prompts, one\-shot prompts, chain-of-thought prompts, and other Prompt Engineering techniques. Work with AWS services (Lambdas, API Gateway, S3, DynamoDB, etc.), ensuring performance and security. Apply generative AI (Gemini, GPT, Claude, etc.) in the development process to optimize code, testing, documentation, and solutions. Actively collaborate across all phases of the development lifecycle, participating in technical discussions and architectural decisions. Apply Clean Code, SOLID, MVC, and DDD principles to ensure solution quality, maintainability, and consistency. Integrate and orchestrate models using tools such as LangChain, CrewAI, or similar frameworks. Contribute to the continuous improvement of processes, architecture, and technical governance of the platform. **Requirements and Qualifications** Collaborative, proactive profile with broad vision regarding product, architecture, and continuous evolution. Proven experience with LLMs (Gemini preferred). Proficiency in Prompt Engineering (persona prompt, one\-shot, chain-of-thought, prompt tuning). Experience with RAG. Solid knowledge of Python (including Lambdas) and .NET Core 8\. Hands-on experience with the AWS ecosystem. Knowledge of Git and best practices in software engineering. Interest and practical experience in applying AI within the development process.


