Senior Software Engineer | AI SaaS Software

New

Based in Brazil, approximately UTC−6 to UTC+2, spanning North American Central Time through Central European Summer TimeFull-TimeSenior

Salary not disclosed

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Job Details

Experience: At least 7 years of professional software engineering experience
Required Skills: AWSPostgreSQLJavascriptRedisReactScalaSaaS

At least 7 years of professional software engineering experience building and maintaining production systems.
Strong backend engineering expertise in Scala or a comparable language such as Java, Ruby, or C#.
Solid JavaScript and React experience developing and maintaining modern frontend applications.
Experience building, scaling, and evolving SaaS products in production.
Deep familiarity with AI-powered coding tools such as Claude Code, Codex, Cursor, or comparable agentic development solutions.
Practical experience with multi-session coding environments and agent-driven workflows, including context management and task coordination.
Strong judgment in evaluating when to use AI-generated solutions versus manual implementation or deeper investigation.
Experience designing systems and architectures.
Ability to build or customize AI-assisted development workflows, internal engineering tools, reusable prompts, and agent-based systems.
Excellent written communication and ability to collaborate effectively in an asynchronous, distributed team.
Availability to work within approximately UTC−6 to UTC+2.

Architect, build, and evolve scalable backend systems using Scala, Play Framework, PostgreSQL, Redis, and AWS.
Design, develop, and deploy reliable APIs and AI-assisted services.
Own end-to-end feature development, including implementation, testing, deployment, and production support.
Build and maintain frontend experiences using React, Chakra UI, Storybook, Redux, React Query, and XState.
Develop agent-driven engineering workflows for coding, debugging, and refactoring.
Use AI coding tools such as Claude Code, Codex, and Cursor while evaluating generated code for quality and maintainability.
Create internal developer tools, reusable prompts, AI skills, and automation systems.
Optimize performance across applications, services, APIs, infrastructure, and AI-assisted development pipelines.
Establish practices for AI-native software development and human-AI collaboration.
Help define technical direction and development practices while progressing toward leading a team of approximately two to three engineers.

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