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 Tech Lead AI Engineer to lead the technical development of AI-powered solutions, combining strong software engineering expertise with hands-on experience in Generative AI and cloud technologies.
In this role, you will be responsible for driving technical decisions, contributing directly to the development of solutions, and acting as a technical reference for the team. You will work across the AI and application stack, helping build scalable, reliable, and production-ready solutions.
Requirements
Advanced English level.
Strong experience in software engineering and previous experience acting as a technical reference or leading engineering teams.
Solid hands-on experience with Python and Django/Django REST Framework.
Practical experience with Azure OpenAI and Generative AI solutions.
Experience with LangChain and integrating LLMs into applications.
Hands-on experience with Celery and Redis for asynchronous processing and distributed tasks.
Experience working with PostgreSQL.
Experience with React and/or Next.js.
Experience with Azure DevOps, including CI/CD pipelines and development workflows.
Experience with Bicep or Infrastructure as Code in Azure environments.
Strong understanding of software architecture and the ability to translate business requirements into technical solutions.
Strong communication and collaboration skills.
Ability to work hands-on while providing technical direction to the team.
Advanced English communication skills.
Nice to Have
Experience designing architectures for LLM-powered applications.
Knowledge of Generative AI application patterns and best practices.
Experience integrating multiple Azure services.
Knowledge of observability, security, and best practices for AI applications in production.
Experience with microservices and distributed systems.
Previous experience mentoring and developing software engineering professionals.