[Job - 32269] Senior AI Engineer, Brazil
Summary
Senior AI Engineer at CI&T joining a delivery team that builds Generative AI and agentic AI solutions for enterprise clients, owning work from technical discovery to production. Hands-on with RAG, AI agents, LLM providers, frameworks like LangGraph/LangChain, plus evaluation, observability, and cloud-native deployment.
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.
You will help shape and deliver AI solutions from discovery to production, combining strong software engineering foundations with modern AI capabilities. The role involves hands-on work with RAG, AI agents, enterprise integrations, intelligent workflows, evaluation, observability, and cloud environments.
What you will do:
- Design and evolve Generative AI, RAG, and agentic applications.
- Define technical approaches considering quality, scalability, security, cost, maintainability, and operational impact.
- Design agents and workflows that interact with tools, APIs, databases, messaging systems, and enterprise platforms.
- Define orchestration patterns such as Human-in-the-Loop, long-running workflows, retries, fallback strategies, and deterministic controls.
- Establish evaluation, observability, guardrails, and reliability practices for AI applications.
- Guide model, retrieval, framework, and infrastructure choices based on technical trade-offs.
- Troubleshoot complex production issues involving models, prompts, retrieval, tools, integrations, and infrastructure.
- Collaborate with architects, engineers, product teams, and business stakeholders, providing technical guidance when needed.
- Support other engineers and contribute to engineering standards and best practices for AI solutions.
Must-have:
- Proven ability to design and deliver production-grade Generative AI and LLM-based solutions.
- Deep knowledge of software design principles, including modularity, separation of concerns, testability, maintainability, resiliency, and clean interfaces.
- Ability to design services, APIs, asynchronous workflows, and distributed components for production environments.
- Hands-on knowledge of RAG and agentic AI patterns, including tool use, function calling, orchestration, Human-in-the-Loop, and guardrails.
- Strong understanding of embeddings, vector search, retrieval strategies, chunking, reranking, and enterprise knowledge retrieval.
- Proficiency with AI frameworks or SDKs such as LangGraph, LangChain, Semantic Kernel, LlamaIndex, OpenAI Agents SDK, Strands, or similar.
- Practical knowledge of multiple LLM providers such as OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI, AWS Bedrock, or similar.
- Ability to assess trade-offs between models, providers, orchestration approaches, retrieval strategies, and infrastructure options.
- Strong knowledge of AI evaluation and observability, including quality, tracing, latency, token usage, failures, and cost.
- Good understanding of cloud-native practices such as scalability, resiliency, secrets management, configuration management, observability, and access control.
- Strong working knowledge of Docker, CI/CD, automated testing, and version control.
- English for technical discussions with international stakeholders.
Nice-to-have:
- Background in Agentic SDLC, coding agents, GitHub, or developer tooling integrations.
- Familiarity with knowledge graphs, GraphRAG, or hybrid retrieval architectures.
- Hands-on knowledge of Datadog LLM Observability, LangSmith, OpenTelemetry, or similar platforms.
Skills
- Agentic AI
- AI
- Anthropic
- API
- AWS
- AWS Bedrock
- Azure
- CI/CD
- Claude
- Cloud
- Cloud Native
- Datadog
- Docker
- Embeddings
- Gemini
- Generative AI
- GitHub
- LangChain
- LangGraph
- LangSmith
- LlamaIndex
- LLM
- Observability
- OpenAI
- OpenTelemetry
- RAG
- SDLC
- Secrets Management
- Semantic Kernel
- Technical Discovery
- Test Automation
- Vector Search
- Version Control
As published by lever · 20 questions
Basics
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