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.
We are seeking talented Generative AI Engineers to join our team and build AI solutions that transform how our clients leverage artificial intelligence. In this role, you'll work at the intersection of software engineering and AI, designing and implementing sophisticated generative AI systems that go beyond simple API integrations. You'll be responsible for architecting scalable AI applications using cutting-edge platforms (such as AWS Bedrock, Gemini, OpenAI SDK, among others), building RAG (Retrieval-Augmented Generation) pipelines, implementing agentic architectures, and creating intelligent solutions that drive real business value.
As a Generative AI Engineer, you'll collaborate with cross-functional teams including product managers, data scientists, solution architects, and other engineers to translate complex business requirements into production-ready AI systems. Your work will directly impact product capabilities, user experience, and our clients' ability to innovate with AI technology.
AI Solution Development & Architecture
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
Backend & Infrastructure Development
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
Prompt Engineering & Model Optimization
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
Collaboration & Innovation
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
Prefered Skills
Strong years of professional software engineering experience
Backend development experience (Full-stack is a differential)
Hands-on experience with
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
Knowledge of DevOps and public cloud practices (Desired CI/CD pipelines for AI applications)
Knowledge of Python with experience in modern frameworks and libraries