Mid Level AI Engineer PL - Java

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Mid Level AI Engineer PL - Java based in Brazil. As an AI Engineer, you will help transform artificial intelligence capabilities into practical, business-focused solutions with real-world impact. You will contribute to building a new Java-based engine using Spring to support AI-powered documentation through Retrieval-Augmented Generation (RAG). The role combines backend engineering with emerging AI technologies, including LLMs, agents, prompt engineering, and retrieval systems. You will design multi-step automations and AI interactions while ensuring quality, security, and reliability in production environments. Working end-to-end, you will collaborate with multidisciplinary teams and adapt to different technology stacks and project requirements. You will have the opportunity to work with modern AI development practices and contribute to innovative, AI-native engineering approaches. This is a strong opportunity for a proactive engineer who enjoys learning, experimenting, and turning new AI capabilities into scalable software. AI-Powered Backend Development: Design and develop a robust Java/Spring engine supporting AI-powered documentation generation and other intelligent application capabilities. AI Agent Development: Implement automations and interactions with technical environments using AI agents capable of executing multi-step tasks. RAG Solutions: Build and integrate Retrieval-Augmented Generation capabilities to provide relevant, contextual information to AI-powered applications. AI Specifications: Structure clear specifications and context for AI models while maintaining appropriate quality, security, and production controls. End-to-End AI Engineering: Contribute across the complete AI development lifecycle, from solution design and implementation through integration, testing, and production deployment. Prompt & Model Integration: Develop effective prompts and integrate appropriate AI models, skills, and supporting technologies into software solutions. AI Architecture: Apply concepts such as Harness Engineering, MCP, token management, AI context, and Software Design Documents to create reliable AI-enabled applications. Cross-Functional Collaboration: Work closely with engineering and project teams to integrate AI capabilities effectively into existing and new technology solutions. Technology Adaptability: Navigate different technology stacks and development environments, adapting technical approaches to the specific needs of each project. Innovation: Explore emerging AI technologies, methodologies, and approaches to continuously improve solution quality and engineering efficiency. Requirements: Professional Experience: Mid-level experience in software engineering or AI engineering, with a strong foundation in backend development. Java Development: Solid experience developing applications with Java; knowledge of the Spring framework is strongly preferred. AI & LLMs: Practical understanding of Large Language Models and how they can be incorporated into production software applications. RAG: Knowledge of Retrieval-Augmented Generation concepts and experience applying retrieval-based approaches to AI solutions. Prompt Engineering: Ability to design and refine effective prompts for interacting with AI models and achieving reliable outputs. AI Agents & Skills: Understanding of AI agents, multi-step task execution, and the development or implementation of AI skills. Modern AI Concepts: Familiarity with MCP, token management, AI context, Harness Engineering, AIDLC, and SDD practices. AI Models: Understanding of different AI models and the ability to select and apply them according to project requirements. Technical Adaptability: Ability to work comfortably across different technologies and technology stacks as project needs evolve. Problem Solving: Strong analytical and problem-solving capabilities,