Full Stack Developer, AI (Mid-Level)

Posted 3hrs ago

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Full Stack Developer with AI focus for SaaS solutions, contributing to engineering and mentorship.

Contribute to robust, sustainable, results-oriented solutions;
Work with technical autonomy, collaborating on planning and mentoring more junior developers;
Help build a software engineering environment guided by quality, performance and continuous improvement;
Use AI tools (such as Windsurf, Copilot, JetBrains AI, Anthropic) to accelerate development and test automation;
Demonstrate a digital mindset, curiosity for new technologies and an interest in understanding how Artificial Intelligence can transform processes, experiences and outcomes;
Work with technologies such as Java, Spring, React, JUnit, Mockito, Git, Hibernate, among others.

Experience with Java 11+ and Spring Framework;
Experience with React.js, including hooks, componentization and integration with REST APIs;
Experience applying SOLID principles and proficiency with Design Patterns;
Practical knowledge of Clean Code and Clean Architecture / Hexagonal Architecture;
Strong experience with unit testing;
Knowledge of TDD (Test-Driven Development);
Experience with relational databases such as PostgreSQL;
Experience with Java application servers, especially WildFly;
Practical experience consuming language models (LLMs) via API, including token management, context windows, temperature control and handling structured outputs (JSON mode);
Experience with AI-native development environments like Codeium, Windsurf and Cursor;
Understanding of how to structure basic CI/CD pipelines for AI and a working knowledge of MLOps principles;
Familiarity with vector databases or Retrieval-Augmented Generation (RAG) techniques;
Knowledge of or interest in AI technologies, their tools, applications and concepts.
Preferred:
Knowledge of Node.js, especially for backend service integration;
Experience participating in technology migration projects or rewrites of legacy systems;
Knowledge of techniques to mitigate “hallucinations” and prompt security best practices;
Practical experience with the model lifecycle (training, evaluation and deployment).