Pessoa Desenvolvedor Back-end Senior (AI Advocate)

BrazilRemoteFull-timesenior

Other

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Quick Summary

Requirements Summary

Extensive experience in back-end software development, with the technical maturity to contribute to complex solutions and architectural decisions.

Technical Tools

Other

We are seeking an experienced back-end developer to build and evolve mission-critical applications with a strong focus on performance, scalability, and availability. In this role, you will combine deep Java expertise with modern cloud-native architectures to deliver robust services and seamless system integrations. Beyond hands-on development, you will champion the adoption of artificial intelligence tools and practices across engineering workflows and client solutions. You will contribute to architectural decisions involving microservices and event-driven systems while promoting high standards of code quality, automated testing, and operational excellence. Working closely with multidisciplinary teams, you will help solve complex technical challenges and share knowledge to strengthen engineering capabilities. This remote opportunity is ideal for a proactive, technically driven professional passionate about software innovation and the practical impact of AI.

Back-end Development: Design, develop, and maintain robust, high-performance back-end applications using Java and the Spring ecosystem, building RESTful APIs and reliable integrations between systems.
AI Advocacy and Adoption: Promote the exploration and adoption of AI-powered tools and solutions across development workflows and products, identifying opportunities to improve productivity, quality, and innovation.
Architecture and Technical Decisions: Contribute to architectural design and technical standards, working with distributed systems, microservices, and event-driven architectures to ensure scalability and resilience.
Code Quality and Testing: Maintain high engineering standards through automated testing, code reviews, clean coding practices, and continuous improvement of software quality.
Technical Problem-Solving: Collaborate with multidisciplinary squads to investigate and resolve complex software engineering challenges, providing technical guidance and sharing best practices.
Cloud-Native Performance: Monitor, troubleshoot, and optimize application performance, reliability, and availability in cloud environments.
DevOps and Delivery: Support modern software delivery practices, including containerization, CI/CD pipelines, and collaboration between development and infrastructure teams.
Continuous Innovation: Evaluate emerging technologies and AI-assisted development practices, helping teams integrate effective solutions into their day-to-day work and deliver greater business value.

Requirements

~1 min read

Professional Experience: Extensive experience in back-end software development, with the technical maturity to contribute to complex solutions and architectural decisions.
Java and Spring: Strong proficiency in Java 11 or later, Spring Boot, and the broader Spring ecosystem.
APIs and Distributed Systems: Hands-on experience designing and developing RESTful APIs, microservices, and distributed software architectures.
Artificial Intelligence Tools: Practical familiarity with AI tools, concepts, and development workflows, including RAG, BMAD, APM, Devin, Claude, GitHub Copilot, and Hive or comparable solutions.
Cloud Computing: Experience developing and operating applications in cloud environments, preferably AWS.
Databases and Messaging: Solid knowledge of relational and NoSQL databases, along with messaging technologies such as Kafka, RabbitMQ, or equivalent platforms.
Containers and DevOps: Strong experience with Docker, Kubernetes, DevOps practices, and CI/CD pipelines.
Automated Testing: Experience creating and maintaining automated tests using frameworks such as JUnit and Mockito.
Analytical and Collaborative Skills: Strong problem-solving abilities, initiative, clear communication, and a collaborative mindset, with the ability to support teams, influence technical decisions, and adapt to evolving engineering challenges.