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CI&T
Brazil

[Job-32047] Mid-Level AI Engineer

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📍 BrazilRemotoPublicada 02 de outubro de 2026capturada em 02/10/2026
ANÁLISE DE COMPATIBILIDADE COM IA

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Descrição da vaga

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 Mid-Level AI Engineer to join a delivery team building Generative AI and Agentic AI solutions for a global enterprise client.
You will work closely with senior engineers, architects, and product teams to build and evolve AI solutions from experimentation to production. The role involves hands-on development with RAG, AI agents, enterprise integrations, conversational AI, and intelligent workflows, supported by solid software engineering practices.

What you will do:

  • Develop and evolve Generative AI and agentic applications.
  • Build RAG-based solutions and enterprise knowledge retrieval components.
  • Implement AI agents that interact with tools, APIs, databases, and enterprise systems.
  • Work with orchestration patterns such as multi-step workflows, tool use, and Human-in-the-Loop.
  • Integrate LLM providers and cloud AI services.
  • Design maintainable and testable components following good software engineering practices.
  • Implement and maintain evaluation, observability, guardrails, and monitoring capabilities.
  • Write automated tests and contribute to CI/CD pipelines.
  • Troubleshoot and improve AI applications in production with support from senior team members.
  • Collaborate with engineers, architects, product teams, and business stakeholders.

    • Must-have:

  • Strong Python development skills and solid software engineering fundamentals.
  • Good understanding of software design principles, including modularity, separation of concerns, testability, maintainability, and clean interfaces.
  • Familiarity with common architectural patterns for APIs, services, asynchronous processing, and distributed applications.
  • Hands-on knowledge of Generative AI and LLM-based application development.
  • Ability to build RAG solutions and/or agentic workflows.
  • Familiarity with tool use, function calling, and workflow orchestration patterns.
  • Proficiency with at least one AI framework or SDK such as LangGraph, LangChain, Semantic Kernel, LlamaIndex, OpenAI Agents SDK, Strands, or similar.
  • Practical knowledge of at least one major LLM provider, such as OpenAI,
  • Anthropic Claude, Google Gemini, Azure OpenAI, AWS Bedrock, or similar.
  • Good understanding of embeddings, vector search, and knowledge retrieval concepts.
  • Familiarity with AI evaluation, observability, guardrails, and production monitoring.
  • Ability to integrate AI applications with APIs, databases, and cloud services.
  • Working knowledge of Docker, CI/CD, automated testing, and version control.
  • English proficiency for daily collaboration with international teams.

    • Nice-to-have:

  • Exposure to multi-agent or long-running agent workflows.
  • Knowledge of Agentic SDLC or developer tooling integrations.
  • Familiarity with knowledge graphs or GraphRAG.
  • Hands-on knowledge of Datadog LLM Observability, LangSmith, OpenTelemetry, or similar platforms.
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