Mid-Level Software Developer
J
JobgetherSoftware Development
BrazilFull-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- AWSAgileRESTful APIsUnit Testing
Requirements
- Strong experience with modern software development practices, version control, and working with existing production codebases.
- Hands-on experience with REST APIs, webhooks, and system integrations.
- Strong understanding of HTTP, request/response patterns, authentication, authorization, and permissions.
- Experience developing unit and/or integration tests and maintaining software quality.
- Strong troubleshooting, analytical thinking, and problem-solving abilities.
- Ability to work independently in an Agile and iterative delivery environment.
- Demonstrated interest or practical experience with AI-assisted software development or Agentic SDLC practices.
- Experience with AI coding agents, agentic development tools, or AI-powered developer workflows is a strong advantage.
- Experience with AWS and cloud-native applications is desirable, particularly serverless technologies such as Lambda and API Gateway.
- Knowledge of identity and access management, event-driven architectures, CI/CD, automated deployments, observability, logging, monitoring, and application diagnostics is a plus.
Responsibilities
- Understand and contribute to an existing webhook-based codebase, architecture, integrations, development practices, and production workflows.
- Develop new functionality, enhancements, and technical improvements while addressing prioritized defects, technical debt, and lower-complexity items.
- Work with REST APIs, webhooks, HTTP request/response patterns, authentication, authorization, permissions, and related integration components.
- Troubleshoot application and integration issues, investigate defects, and use structured approaches to identify root causes.
- Develop and maintain unit and integration tests while continuously improving code quality, reliability, and maintainability.
- Participate in code reviews and contribute to engineering standards, development practices, and technical documentation.
- Use AI agents and agentic development tools to accelerate codebase discovery, dependency analysis, application-flow tracing, implementation, refactoring, debugging, test generation, and documentation.
- Critically review and validate AI-generated code to ensure it meets required standards for security, reliability, quality, and maintainability.
- Collaborate with Product and QA teams to clarify requirements, prioritize work, investigate defects, and validate delivered solutions.
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