
5001 - 10000 employees
Founded 1995
🤖 Artificial Intelligence
☁️ SaaS
💰 $5.5M Venture Round on 2014-04
Artificial Intelligence • Cloud Services • SaaS
CI&T is a global tech transformation specialist focusing on helping organizations navigate their technology journey. With services spanning from application modernization and cloud solutions to AI-driven data analytics and customer experience, CI&T empowers businesses to accelerate their growth and maximize operational efficiency. The company emphasizes digital product design, strategy consulting, and immersive experiences, ensuring a robust support system for enterprises in various industries.
🔥 3 minutes ago
🗣️🇧🇷🇵🇹 Portuguese Required
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5001 - 10000 employees
Founded 1995
🤖 Artificial Intelligence
☁️ SaaS
💰 $5.5M Venture Round on 2014-04
Artificial Intelligence • Cloud Services • SaaS
CI&T is a global tech transformation specialist focusing on helping organizations navigate their technology journey. With services spanning from application modernization and cloud solutions to AI-driven data analytics and customer experience, CI&T empowers businesses to accelerate their growth and maximize operational efficiency. The company emphasizes digital product design, strategy consulting, and immersive experiences, ensuring a robust support system for enterprises in various industries.
• Work across the full development cycle (design → build → test → deploy → operate) with AI support • Use agents and automations to execute multi-step tasks • Structure inputs (prompts, specs) to guide and control AI • Integrate with engineering tools: Git, CI/CD, observability • Evaluate the quality and safety of AI-generated outputs • Understand the architecture behind generated solutions, not just operate the tools
• Backend development with .NET (REST APIs, microservices) • Messaging and asynchronous processing (Kafka, SQS, event-driven architectures) • Strong expertise in AWS Cloud (S3, EC2, Lambda, SQS, DynamoDB, etc.) • Experience with relational and NoSQL databases • Distributed systems architecture (DDD, decoupling, resilience, scalability) • Software quality (unit and integration testing, best practices) • Knowledge of AI-centered methodologies (SDD, AI-DLC, etc.) • Advanced use of AI in development (code generation, testing, refactoring, debugging) • Building agents (multi-step workflows, tool usage, planning and execution) • Creating reusable skills and composing capabilities • Integration via MCP (Model Context Protocol) or equivalent • Orchestration of workflows (multi-agent or human + agent) • Integration with tools (Git, CI/CD, issue tracking, observability) • Critical evaluation of AI outputs (quality, safety, consistency)
• If you like it, apply and good luck! • #LI-GV1 • #Senior
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