The Role
Develop and productionize generative AI and agentic applications, including RAG systems, AI agents, conversational AI, and intelligent workflows. Integrate LLM providers, APIs, databases, cloud services, and enterprise systems. Build evaluation, observability, guardrail, monitoring, testing, and CI/CD capabilities while applying strong software engineering practices. Collaborate with senior engineers, architects, product teams, and international stakeholders to troubleshoot and improve AI solutions.
Summary Generated by Built In
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.
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.
Our benefits:
-Health and dental insurance
-Meal and food allowance
-Childcare assistance
-Extended paternity leave
-Partnership with gyms and health and wellness professionals via Wellhub (Gympass) TotalPass;
-Profit Sharing and Results Participation (PLR);
-Life insurance
-Continuous learning platform (CI&T University);
-Discount club
-Free online platform dedicated to physical, mental, and overall well-being
-Pregnancy and responsible parenting course
-Partnerships with online learning platforms
-Language learning platform
And many more!
More details about our benefits here: https://ciandt.com/br/pt-br/carreiras
At CI&T, inclusion starts at the first contact. If you are a person with a disability, it is important to present your assessment during the selection process. See which data needs to be included in the report by clicking here.This way, we can ensure the support and accommodations that you deserve. If you do not yet have the assessment, don't worry: we can support you in obtaining it.
We have a dedicated Health and Well-being team, inclusion specialists, and affinity groups who will be with you at every stage. Count on us to make this journey side by side.
Skills Required
- Strong Python development skills and solid software engineering fundamentals
- Understanding of software design principles, including modularity, separation of concerns, testability, maintainability, and clean interfaces
- Familiarity with 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
- 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
- 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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The Company
What We Do
CI&T is your end-to-end digital transformation partner. As a digital native, we bring a 27-year track record of accelerating business impact through complete and scalable digital solutions. With a global presence of 6,000+ professionals in strategy, research, data science, design and engineering, we unlock top-line growth, improve customer experience and drive operational efficiency.
