[Job-32046] Senior AI Engineer at CI&T

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. What you will do: - Own AI solutions from technical discovery through production and continuous improvement. - 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: - Strong Python development skills and solid software engineering foundations. - 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. - Fluent English for technical discussions with international stakeholders. Nice-to-have: - Knowledge of multi-agent systems and long-running agent workflows. - 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. 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 res