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Brasil
Remote only
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.
At CI&T, we are looking for a Senior GenAI Engineer to join our global team and help design, build, and scale advanced Generative AI and Agentic AI solutions for enterprise clients.
This role is ideal for a professional with deep hands-on experience in Generative AI, LLMs, RAG, and agent-based architectures, combined with strong software engineering, cloud, and production-grade AI platform expertise.
You will work on the development of secure, scalable, observable, and reliable AI applications that support complex business workflows and large-scale enterprise environments.
Design, develop, and maintain GenAI and Agentic AI applications for production environments.
Build customizable agent solutions using frameworks such as LangChain, DeepAgents, Strands AI, or similar Agent SDKs.
Develop production-grade Python tooling and reusable AI components.
Implement RAG pipelines, external knowledge integrations, memory management, and context orchestration strategies.
Design secure sandboxed execution environments for agent tooling, including permissions, secrets management, network restrictions, and auditability.
Build and maintain MCP (Multi-Cloud Platform) tooling, including authentication, schema design, versioning, retries, and safe execution boundaries.
Implement observability, tracing, logging, and monitoring for prompts, tool calls, model performance, latency, and cost optimization.
Create automated evaluation and testing frameworks for AI agents, including golden datasets, regression tests, hallucination detection, and quality gates.
Design human-in-the-loop approval workflows for sensitive or high-risk operations.
Manage prompt versioning, model routing, fallback strategies, and token/cost optimization for enterprise AI systems.
Collaborate with Data, Analytics, Platform Engineering, and business stakeholders to deliver scalable AI solutions aligned with business goals.
Advanced / Fluent English (C1 or higher), mandatory.
Experience working with international clients and global teams.
Strong hands-on experience with Generative AI, LLMs, RAG, and agent-based architectures.
Proficiency in Python and software engineering best practices.
Experience designing secure, scalable, and production-ready AI systems.
Solid understanding of AI model evaluation, deployment, observability, and operational reliability.
Experience with agent execution pipelines, CI/CD integrations, backend AI workflows, and automated orchestration.
Strong knowledge of prompt engineering, context management, hallucination mitigation, and knowledge freshness strategies.
Ability to work autonomously in complex, fast-paced, and ambiguous environments.
Experience with Azure, AWS, or GCP, especially deploying Generative AI solutions in cloud environments.
Familiarity with Databricks, Vertex AI, Azure OpenAI, Amazon Bedrock, or similar enterprise AI platforms.
Experience with Docker, Kubernetes, and containerized AI workloads.
Knowledge of MLOps and AI/ML pipeline automation.
Understanding of AI security, governance, compliance, and data privacy regulations.
Certifications related to Generative AI, Machine Learning, Cloud, or AI Engineering.
At CI&T, you will work on large-scale AI transformation initiatives for global clients, collaborating with highly skilled engineers, architects, and AI specialists. You will have the opportunity to influence technical strategy, build cutting-edge Agentic AI platforms, and contribute to innovative solutions that create real business impact in a collaborative, growth-oriented, and technology-driven environment.
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