[Job-00023] Senior AI Engineer, Brazil

Ciandt

Job details

  • REMOTE
  • UNKNOWN
  • Brazil
  • Brazil
  • Verified 2026-10-09
  • Source: Ciandt public LEVER source

Original 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.


We are looking for a Senior AI Engineer to design and develop AI-powered solutions that combine Large Language Models (LLMs), document intelligence, and full-stack engineering.

In this role, you will build reliable information extraction pipelines, improve the accuracy and traceability of AI-generated results, and contribute to the evolution of a web application. You will work across AI engineering, model evaluation, and front-end development to deliver scalable solutions that meet business requirements and provide a high-quality user experience.

Responsibilities
  • Design and develop LLM-powered extraction pipelines using techniques such as multi-call consensus, grounding, and value verification to improve accuracy and reliability.
  • Align extracted attributes with the PriCat standard, ensuring data consistency and compatibility with new ERP systems.
  • Evaluate and optimize AI models based on accuracy, cost, and latency, using LLM observability tools to monitor and improve performance.
  • Develop and integrate AI capabilities using Python, Azure OpenAI, LangChain, and Document Intelligence.
  • Build and maintain prompt templates and structured generation workflows using Jinja2.
  • Rebuild and enhance the web application based on the Design team's mockups, using Next.js and React.
  • Implement user-facing features such as PDF grounding views to improve transparency and help users validate extracted information.
  • Support French-speaking users by investigating and resolving issues, delivering fixes, and implementing small features.
  • Develop and maintain automated tests to ensure application quality, reliability, and maintainability.
  • Collaborate with engineering, design, and business stakeholders to translate requirements into effective AI-powered solutions.
Requirements for this challenge
  • Strong experience in software engineering, with a focus on AI engineering and full-stack development.
  • Proficiency in Python and experience building AI-powered applications.
  • Hands-on experience with Azure OpenAI and Large Language Models (LLMs).
  • Experience with LangChain and developing LLM-based workflows or information extraction pipelines.
  • Knowledge of document processing, structured data extraction, grounding, and output validation.
  • Experience evaluating AI solutions against quality, cost, and latency metrics.
  • Familiarity with LLM observability tools, particularly Langfuse.
  • Experience with React and Next.js for front-end development.
  • Familiarity with Jinja2 or similar template-based approaches.
  • Experience implementing automated tests and troubleshooting production applications.
  • Strong analytical and problem-solving skills, with attention to data quality and reliability.
  • Ability to collaborate with multidisciplinary teams and communicate technical concepts clearly.
Nice to Have
  • Experience with Azure AI Document Intelligence or similar document processing technologies.
  • Knowledge of LLM evaluation strategies, multi-step extraction, consensus mechanisms, and grounding techniques.
  • Experience integrating AI-generated data with ERP systems or enterprise data standards.
  • Familiarity with PDF rendering, document annotation, and evidence-based validation interfaces.
  • Experience supporting international users or working in multilingual environments.
  • Knowledge of AI application monitoring, tracing, and continuous improvement practices.
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