[Job-30774] Master IA Developer, Brazil

At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.

With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.

We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.

Design and implement agentic workflows using multi-agent frameworks and Large Language Model (LLM) APIs.
Define architectural patterns for AI-powered applications, ensuring scalability, reliability, maintainability, and security.
Develop and evolve AI solutions using Python and modern software engineering practices.
Collaborate with engineering teams to enhance internal AI platforms, developer tooling, and reusable capabilities.
Drive the adoption of AI development methodologies such as BMAD, Specification-Driven Development (SDD), or similar approaches.
Support production environments by applying observability, reliability, and incident response best practices.
Perform code reviews, mentor engineers, and contribute to technical decision-making across teams.
Continuously improve platform architecture, engineering standards, and software quality.

Solid experience developing applications with Python.
Experience building solutions powered by Generative AI and Large Language Models (LLMs).
Hands-on experience designing and implementing agentic workflows using multi-agent frameworks.
Experience integrating applications with LLM APIs and AI services.
Strong understanding of software architecture, distributed systems, and scalable application design.
Experience with software engineering best practices, code reviews, testing, and CI/CD.
Knowledge of observability, production support, and system reliability practices.
Ability to provide technical leadership and collaborate across multidisciplinary teams.
Advanced English communication skills.

Experience with LangGraph, LangChain, CrewAI, AutoGen, or similar frameworks.
Knowledge of Agentic AI architectures and multi-agent systems.
Experience with AI development methodologies such as BMAD or Specification-Driven Development (SDD).
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Knowledge of Docker, Kubernetes, and cloud-native architectures.
Experience with Site Reliability Engineering (SRE), monitoring, and observability tools.
Experience building AI platforms, developer tools, or reusable AI infrastructure.