Software Architect AI SDLC

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Architect AI SDLC based in Brazil. This role offers the opportunity to shape the future of software development by integrating generative AI and agentic workflows into the Software Development Life Cycle (SDLC). You will design, implement, and evolve AI-driven workflows that support development teams across analysis, testing, deployment, and delivery. The position combines software architecture, cloud engineering, DevOps, and practical applications of generative AI. You will work closely with technical stakeholders to turn AI capabilities into secure, scalable, and production-ready solutions. A key focus will be optimizing AI agents while maintaining high standards for quality, security, compliance, and reliability. You will contribute to an evolving AI infrastructure roadmap and help identify opportunities to automate development processes. The role is fully remote, with office attendance required for professionals living in the Campinas metropolitan area according to the applicable policy. Accountabilities - Design, implement, and continuously improve agentic workflows that transform software development processes through AI. - Customize and configure generative AI platforms according to SDLC requirements, including skills, personas, prompts, and contextual information. - Develop and maintain AI-driven workflows integrated with development pipelines such as Azure DevOps, Git, and CI/CD environments. - Integrate AI agents across multiple stages of the SDLC, including analysis, requirements refinement, development, testing, and deployment. - Tune agent parameters, strategies, and workflows to optimize performance and output quality at each stage of development. - Plan and execute the AI infrastructure roadmap in collaboration with relevant technical stakeholders. - Automate software development activities while maintaining quality, security, compliance, and engineering standards using practices and tools such as SonarQube, Veracode, and test coverage.

- Identify, assess, and mitigate technical risks associated with deploying AI agents in production environments. - Ensure AI-enabled solutions follow appropriate ethical, security, regulatory, and governance standards. - Collaborate across teams and contribute to the continuous improvement of AI-assisted software engineering practices. Requirements - Solid professional experience in software development using Java, Python, or similar programming languages . - Experience with CI/CD pipelines and DevOps practices, particularly Azure DevOps, GitFlow, and SonarQube . - Practical cloud computing experience, especially with AWS services such as Lambda, SQS, and S3 . - Hands-on experience with generative AI tools applied to software development, such as Claude Code, GitHub Copilot, or similar technologies . - Ability to write, refine, and review prompts, configure AI agents, and evaluate the quality and reliability of AI-generated outputs. - Strong understanding of software quality practices, including automated testing, BDD, and SAST. - Strong architectural and problem-solving capabilities, with the ability to evaluate technical risks and design scalable solutions. - Ability to work collaboratively with technical teams while communicating complex concepts clearly. - Experience with agentic frameworks or methodologies such as AISDD, Spec-Kit, or similar is a plus. - Knowledge of microservices architectures and technologies such as Spring Boot or Quarkus is desirable. - Familiarity with flow observability tools such as Flow Ops, Databricks, or similar platforms is an advantage. - Experience working on large-scale initiatives involving multiple teams or squads simultaneously is a plus. - Previous experience in the benefits sector or fintech is desirable.