DjangoDockerERPFlaskJavaScriptNext.jsNode.jsNoSQLPostgresPythonReactRubyRuby on RailsSQLTypeScriptGoGolangRAIGenerative AIOpenAIClaudeGeminiRAGLangChainData LakeFastAPIRailsPostgreSQLGitCRMCI/CD
About this role
Role Overview
Work on developing and evolving intelligent web applications, integrating generative AI features and advanced language models to enhance company processes, automations, and digital experiences.
Build scalable and secure solutions that connect internal systems (ERP, CRM, Data Lake) to AI and automation services, applying software engineering best practices, API integration, and data handling.
Explore and prototype new AI use cases in partnership with business areas, contributing to technological innovation and operational efficiency at Crédito Real.
Develop and evolve web applications that incorporate generative AI capabilities such as ChatGPT, Gemini, Claude and LLMs like Llama3, applying these technologies in chatbots, internal assistants, intelligent automations and data analysis.
Create and consume APIs that connect internal systems (ERP, CRM, Data Lake) to AI and automation services.
Apply the Model Context Protocol (MCP) to connect language models to databases, APIs and corporate repositories in a secure, contextual manner.
Work with data and integrations — structuring, processing and connecting information for use in models and intelligent workflows.
Prototype and validate new AI use ideas together with business teams.
Ensure quality, security and scalability in the solutions developed.
Requirements
Proven experience in Full Stack development, with proficiency in at least two of the following languages/frameworks:
JavaScript / TypeScript (Node.js, React, Next.js)
Python (FastAPI, Flask or Django)
Ruby on Rails
Go (Golang)
Experience consuming and integrating REST APIs.
Experience with SQL, NoSQL and vector databases (PostgreSQL, NocoDB, etc.).
Hands-on experience with applied AI, including the use of OpenAI, Copilot and Llama3 for process automation, text analysis and building intelligent assistants, as well as knowledge of language models, embeddings, RAG, LangChain and other AI automation tools.
Familiarity with Docker, Git and CI/CD pipelines.
Experience combining traditional development with no-code/low-code solutions (Bolt, n8n).