À propos de ce poste [Job-30817] Senior AI Engineer, Brazil chez Ciandt
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 looking for a Senior AI Engineer to join our team and help build the next generation of AI-powered products and solutions.
In this role, you will leverage Generative AI as the foundation of software engineering, applying AI across the entire product development lifecycle, from requirements and design to deployment, monitoring, and continuous optimization. You will design and build intelligent agents, implement advanced AI architectures, and collaborate with cross-functional teams to deliver innovative, scalable, and production-ready solutions.
Requirements
- Bachelor's degree in Computer Science, Engineering, Applied Mathematics, or a related field.
- Strong software engineering experience using Python or a similar programming language.
- Hands-on experience with Generative AI frameworks, APIs, and modern LLM ecosystems.
- Proven experience building AI Agents and agentic workflows using Prompt Engineering, Context Engineering, AI Steering, RAG, and Model Context Protocol (MCP).
- Experience with LLMOps, LLM observability, tracing, and evaluation frameworks.
- Solid understanding of AI security practices, including guardrails, prompt injection mitigation, and secure data integration.
- Experience with Agent-to-Agent (A2A) and Agent Coordination Protocol (ACP).
- Experience deploying AI solutions throughout the software development lifecycle, from design to production and monitoring.
- Understanding of short- and long-term memory implementation in AI agents.
- Experience working in cloud-native environments.
- Strong communication skills in English, with the ability to engage both technical and business stakeholders.
- Ability to work independently while collaborating effectively in cross-functional teams.
Nice to Have
- Experience with reasoning strategies such as Chain of Thought and ReAct.
- Hands-on experience with Agentic AI frameworks and multi-agent orchestration tools such as LangGraph or CrewAI.
- Experience with LLM optimization, fine-tuning, and production inference deployment.
- Experience developing custom Model Context Protocol (MCP) servers.
- Knowledge of Knowledge Graphs and Hybrid RAG architectures.
- Experience designing and implementing LLM evaluation frameworks.
- Experience monitoring AI systems for performance, accuracy, reliability, and cost optimization.
