[Job-32533] Senior - AI Engineer
At a glance
- Salary
- Not published
- Location
- Brazil
- Work type
- Remote
- Level
- Senior
- Posted
- today
- Verified live
- today
- Skills
- RAGMulti-agentOrchestrationEval harnesses
- Filed under
- RAG / RetrievalAI AgentsEvals & Quality
How the pay compares
This posting doesn't publish pay. 133 of the 347 Senior AI Agents roles worldwide on this board do: the middle half pay $160k–$222k, with a median of $202k. Too few roles in Brazil publish pay for a local comparison, so this is every country together — mostly US pay.
Middle half of the 133 that publish payMedian10th–90th percentileAnnual, USD
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Job description
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.
Architect and build the software solution that meets the client's demand, in any stack, from architecture to tested code, using the agentic SDLC as the way of working and AI as the main build lever, and remaining accountable for the application delivered in production. Builds and orchestrates their own agents, skills, subagents, commands and harness that accelerate building the application and reuses them across the team, instead of consuming assistants passively. Answers for the quality and the delivery of what they produce, applying critical judgment to AI-generated outputs and pragmatic technical design to avoid overly complex solutions, grounded in modern software architectures, instrumenting observability at system level and using applied AI as a supporting repertoire, focusing on fine-tuning models rather than training them from scratch. When the client's solution includes an AI component, consumes foundation models through APIs and assembles the solution with RAG, tool orchestration, evals and multi-agent designs, structuring the engineering and configuring the context data pipelines and the orchestration and runtime frameworks the agents run on. Uses evals to assess both the probabilistic behavior of the solution and the agents built to accelerate development.