AI Engineer (Mid Level Developer Backend Java)

BrazilRemoteFull-timemid

Machine Learning EngineerData

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Requirements Summary

Contribute to all phases of software development, including planning, requirements analysis, architectural design, coding, testing, deplo

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Machine Learning EngineerData

We are seeking a skilled Java Backend Developer to build scalable, high-performance software solutions while integrating cutting-edge Generative AI technologies into the software development lifecycle. In this role, you will design and maintain robust backend systems and RESTful APIs using Java and Spring Boot, connecting applications with Large Language Models (LLMs). You will contribute to modernizing development workflows through AI-powered tools, automation, and intelligent coding practices. Working in an agile, collaborative environment, you will help transform business requirements into reliable technical solutions. You will also play a key role in improving software quality, delivery efficiency, and operational performance through engineering best practices. This remote opportunity is ideal for a developer passionate about backend engineering, AI innovation, and continuous improvement.

Software Development Lifecycle (SDLC): Contribute to all phases of software development, including planning, requirements analysis, architectural design, coding, testing, deployment, and ongoing maintenance, ensuring high-quality deliverables.
Backend Development and AI Integration: Design, develop, and maintain resilient backend systems and RESTful APIs using Java and Spring Boot, integrating applications with Large Language Models (LLMs) and Generative AI solutions.
AI-Powered Workflow Optimization: Implement and optimize algorithms, automation processes, and AI-assisted coding tools to streamline development activities, including code generation, automated testing, and technical documentation.
Requirements Analysis and Collaboration: Participate in requirements refinement sessions, translate business needs into effective technical solutions, and collaborate with cross-functional teams during agile ceremonies, contributing to estimates of time and resources.
Architecture, Messaging, and Data Management: Apply established architectural principles, including microservices and design patterns, while developing efficient data flows using SQL and NoSQL databases and messaging systems such as Kafka or RabbitMQ.
Code Quality and Testing: Maintain software reliability through automated unit, integration, and end-to-end testing, using tools such as JUnit and Mockito. Participate in code reviews and apply Clean Code principles and established engineering standards.
DevOps and Continuous Delivery: Work with containerized environments using Docker and Kubernetes, supporting CI/CD practices to enable reliable deployments and seamless integration of new technologies.
Troubleshooting and Observability: Investigate, diagnose, and resolve complex technical issues involving code, data, and production environments.
Documentation and Continuous Improvement: Maintain clear technical documentation, share knowledge, and stay informed about emerging technologies and industry best practices to continuously improve solutions and workflows.

Requirements

~2 min read

Professional Experience: Relevant experience in backend software development with Java, ideally using Spring Boot to build scalable, maintainable, and high-performance applications.
Backend Technologies: Solid knowledge of RESTful API development, microservices architecture, and common software design patterns.
Artificial Intelligence: Interest in or experience with Generative AI, Large Language Models (LLMs), and AI-assisted development tools, including their practical application across the software development lifecycle.
Databases and Messaging: Experience working with SQL and NoSQL databases, as well as messaging technologies such as Kafka or RabbitMQ.
Testing and Code Quality: Familiarity with automated testing practices, including unit, integration, and end-to-end testing, and tools such as JUnit and Mockito. Understanding of Clean Code principles and code review practices.
DevOps and Infrastructure: Experience with Docker, Kubernetes, CI/CD pipelines, and containerized development or deployment environments.
Agile Methodologies: Ability to collaborate effectively in agile teams, participate in refinement sessions, contribute to technical estimates, and translate business requirements into functional solutions.
Analytical and Problem-Solving Skills: Strong critical thinking and troubleshooting abilities, with the capacity to investigate complex technical problems and deliver effective solutions.
Communication and Collaboration: Clear communication skills, a collaborative mindset, and the ability to document technical decisions and work effectively with different stakeholders.
Continuous Learning: Proactive approach to professional development, with a strong interest in emerging technologies, AI innovation, and software engineering best practices.
Location and Work Arrangement: Must be based in Brazil. The position is remote; however, candidates residing in the Campinas Metropolitan Region are required to attend the local offices in accordance with the applicable attendance policy.