Senior Java Developer – AI
New
C
CI&TFinancial Services
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English (technical)
- Required Skills
- AWSGitJavaTypeScriptReactCI/CDRESTful APIsMicroservicesPrompt EngineeringGenerative AI
Requirements
- Solid experience with backend development using Java and microservices architecture.
- Experience with frontend development using React and JavaScript or TypeScript.
- Experience with REST APIs, BFF, system integration, and distributed architectures.
- Experience with AWS and application development in Cloud environments.
- Solid knowledge of automated testing, including unit and integration tests.
- Experience with Git, CI/CD, and continuous delivery practices.
- Practical experience with Generative AI and AI agents applied to software development.
- Experience with AI Coding tools like Claude Code, GitHub Copilot, Cursor, or CI&T Flow.
- Knowledge of Prompt Engineering applied to code generation, testing, analysis, and documentation.
- Ability to critically review AI-generated outputs for architecture, security, and performance issues.
- Autonomy to investigate and solve complex technical problems.
- Strong communication and the ability to collaborate and influence technical decisions.
- Technical English for documentation and interaction with AI tools and agents.
Responsibilities
- Develop and evolve applications using Java in the backend and React in the frontend.
- Build and integrate microservices, REST APIs, BFFs, and integrations with external systems.
- Utilize and orchestrate AI agents throughout specification, development, testing, and deployment stages.
- Review, validate, and evolve code and artifacts produced by AI agents to ensure quality and security.
- Participate in refinements to contribute to solution definitions, estimates, and technical risk identification.
- Implement and evolve automated tests including unit, integration, regression, and performance tests.
- Investigate and resolve complex issues related to code, integrations, data, or environments.
- Implement AI automations to increase productivity, quality, and efficiency in the development cycle.
- Collaborate with technical leadership to evolve development practices and the Agentic SDLC model.
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