[Job- 31057] Master Generative AI 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, develop, and deploy production-ready applications using Large Language Models (LLMs), including GPT, Gemini, Claude and other foundation models through AWS Bedrock

• Build and optimize sophisticated RAG (Retrieval-Augmented Generation) architectures that can process and retrieve information from large-scale document repositories

• Implement and orchestrate multi-agent AI systems using AWS Bedrock Agents and AgentCore frameworks

• Design scalable AI pipelines that integrate with enterprise systems and maintain performance at production scale

• Develop robust backend services and APIs for AI applications using Python and modern frameworks

• Implement containerization and deployment strategies for AI applications

• Build monitoring and observability solutions to track AI system performance, quality, and costs

• Design and optimize high-quality prompts and templates that guide LLM behavior and responses

• Implement advanced prompt engineering techniques to maximize model performance and accuracy

• Evaluate and fine-tune models for specific use cases when appropriate

• Continuously experiment with different model configurations, hyperparameters, and architectures

• Partner with vertical areas and stakeholders to understand requirements and translate them into technical solutions

• Stay current with the latest advancements in generative AI research and evaluate emerging foundation models

• Contribute to technical documentation, best practices, and knowledge sharing within the team

• Participate in Sales initiatives related to Generative AI

• Large Language Models (LLMs) and foundation model APIs

• Agentic Architecture & Implementation (e.g., LangChain, LlamaIndex, CrewAI, AutoGen)

• Prompt engineering and optimization techniques

• Data consumption for agentic with Vector databases (e.g., Pinecone, Weaviate, OpenSearch) and embedding models or Knowledge Graph