AI Engineer (Mid-Level Backend Java Developer)
J
JobgetherSoftware development
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.Full-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- DockerSQLJavaKafkaSpring BootNosqlRESTful APIsMicroservicesGenerative AI
Requirements
- Have relevant experience in backend software development with Java; Spring Boot experience is preferred.
- Have knowledge of RESTful API development, microservices architecture, and common software design patterns.
- Have an interest in or experience with Generative AI, Large Language Models, and AI-assisted development tools.
- Have experience with SQL and NoSQL databases and messaging technologies such as Kafka or RabbitMQ.
- Be familiar with unit, integration, and end-to-end testing, including JUnit and Mockito.
- Understand Clean Code principles and code review practices.
- Have experience with Docker, Kubernetes, CI/CD pipelines, and containerized development or deployment environments.
- Be able to collaborate in agile teams, participate in refinement sessions, contribute technical estimates, and translate business requirements into functional solutions.
- Have critical-thinking and troubleshooting abilities to investigate complex technical problems.
- Be able to document technical decisions and work effectively with different stakeholders.
- Be based in Brazil; candidates residing in the Campinas Metropolitan Region are required to attend local offices in accordance with the applicable attendance policy.
Responsibilities
- Contribute to planning, requirements analysis, architectural design, coding, testing, deployment, and maintenance across the SDLC.
- Design, develop, and maintain backend systems and RESTful APIs using Java and Spring Boot.
- Integrate applications with Large Language Models and Generative AI solutions.
- Implement and optimize AI-assisted coding tools, algorithms, and automation for code generation, testing, and documentation.
- Translate business requirements into technical solutions and collaborate with cross-functional teams in agile ceremonies.
- Develop data flows using SQL and NoSQL databases and messaging systems such as Kafka or RabbitMQ.
- Maintain software quality through automated tests, code reviews, Clean Code principles, and engineering standards.
- Support containerized environments and CI/CD practices using Docker and Kubernetes.
- Investigate and resolve technical issues involving code, data, and production environments.
- Maintain technical documentation, share knowledge, and improve solutions and workflows.
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