Software Architect AI SDLC Senior

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 Senior based in Brazil.

As a Software Architect AI SDLC Senior, you will help transform the software development lifecycle through generative AI and agentic engineering practices.

You will design, implement, and evolve AI-powered workflows that automate and enhance development activities from analysis through deployment.

The role combines software engineering, AI infrastructure, cloud technologies, DevOps, and solution architecture in a highly collaborative environment.

You will work closely with development squads and client stakeholders, translating business and technical challenges into scalable AI-enabled solutions.

You will build custom agents, integrate them with delivery pipelines, and establish the infrastructure needed to bring AI-driven automation into production.

Quality, security, compliance, responsible AI practices, and operational reliability will be central to the solutions you design and implement.

This is an opportunity to play a key technical role in an AI transformation program while helping teams adopt new ways of engineering and delivering software.

Accountabilities:

• Design, customize, configure, and continuously improve generative AI platforms for specific software development lifecycle needs, including skills, personas, prompts, and contextual configurations.
• Develop and maintain agentic workflows integrated with development and delivery pipelines using technologies such as Azure DevOps, Git, and CI/CD.
• Integrate AI agents across multiple stages of the SDLC, including analysis, requirements refinement, development, testing, and deployment.
• Tune agent parameters, prompts, and strategies to achieve optimal performance and reliable outcomes at each stage of the development lifecycle.
• Plan and execute the AI infrastructure roadmap in close collaboration with the AI Orchestrator and other technical stakeholders.
• Automate development activities while maintaining rigorous standards for code quality, security, testing, and compliance through 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 that AI-powered solutions follow appropriate ethical, regulatory, security, and governance standards.
• Work cross-functionally with multiple development squads, contributing to technical discussions, solution design, troubleshooting, and production incident resolution.
• Act as a technical partner to client stakeholders, helping translate objectives into effective AI-enabled engineering solutions and facilitating the adoption of agentic practices.
• Promote engineering and AI knowledge sharing across teams and contribute to a culture of continuous learning and innovation.

Requirements:

• Solid professional experience in software development using Java, Python, or comparable programming languages.
• Practical familiarity with CI/CD pipelines and DevOps practices and tools, particularly Azure DevOps, GitFlow, and SonarQube.
• Hands-on experience with cloud computing, especially AWS services such as Lambda, SQS, and S3.
• Practical experience with generative AI tools applied to software development, such as Claude Code, GitHub Copilot, or similar solutions.
• Ability to write, review, and optimize prompts, configure AI agents, and evaluate the quality, reliability, and relevance of their outputs.
• Strong understanding of software quality practices, including automated testing, Behavior-Driven Development (BDD), and Static Application Security Testing (SAST).
• Excellent communication and stakeholder management skills, with the ability to understand client objectives, challenge assumptions constructively, and propose appropriate technical solutions.
• Proactive, resilient, and adaptable mindset, with the ability to work transversally across multiple teams, projects, and technical contexts.
• Genuine interest in generative AI and agentic models, with enthusiasm for continuously learning and sharing knowledge with engineering teams.
• Experience with agentic frameworks and methodologies such as AISDD, Spec-Kit, or similar approaches is an advantage.
• Knowledge of microservices architecture and frameworks such as Spring Boot or Quarkus is a plus.
• Familiarity with flow observability tools such as Flow Ops, Databricks, or similar technologies is desirable.
• Experience working on large-scale initiatives involving multiple teams or squads simultaneously is beneficial.
• Previous experience in benefits-related businesses or fintech environments is considered an advantage.

Benefits:

• Health and dental insurance.
• Meal and food allowance.
• Childcare assistance.
• Extended parental leave.
• Access to fitness, health, and wellness professionals through Wellhub and TotalPass partnerships.
• Profit Sharing and Results (PLR) participation.
• Life insurance.
• Continuous learning opportunities through a dedicated corporate learning platform.
• Access to online courses and professional development resources.
• Language learning platform.
• Discounts through partner programs and benefit clubs.
• Online resources dedicated to physical health, mental health, and overall well-being.
• Courses focused on pregnancy and responsible parenthood.
• Support from dedicated health and well-being teams and inclusion specialists.
• Opportunities to participate in affinity groups and an inclusive workplace culture.
• If based in the Campinas Metropolitan Region, attendance at offices in the city is required according to the applicable workplace attendance policy.