[Job-29944] AI Engineer Senior (AI RAG/Javascript/React)
CI&T
Sobre a vaga
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.
About the Role We’re looking for a Senior Artificial Intelligence Engineer to join our Technology team. You will be a technical reference in designing, architecting, and delivering scalable Generative AI solutions, acting as a bridge between technical innovation, data security, and business impact. You'll work within a stable team, owning the architecture and evolution of our AI solutions over time. The ideal candidate combines strong cloud experience (especially AWS), hands-on expertise in LLMs, AI agents, and Generative AI architectures, a security-first mindset, and the maturity to make architectural decisions independently while providing technical guidance to other team members. Responsibilities * Technical Leadership: Define architecture standards for Generative AI solutions, driving design decisions that impact multiple squads and products. * Conversational Solutions Development: Design, develop, and integrate end-to-end AI solutions with a focus on scalability and maintainability. * AI Agents & Automation: Build and evolve AI agents and intelligent automations, including multi-agent workflows where applicable, to solve real business and engineering problems at scale. * AI-Assisted Engineering: Explore and implement AI-assisted development practices (code generation, refactoring, testing assistance) to improve our own software development lifecycle. * AI Security & Governance: Define and implement robust security strategies for language models, with a special focus on mitigating risks such as prompt injection and sensitive data leakage (ensuring compliance with healthcare/HIPAA regulations). * System Integration: Connect Generative AI models with internal APIs, establishing reusable integration patterns for the team. * POC Lifecycle Management: Lead POCs from technical ideation through validation, QA, and production transition, including feasibility assessment and architecture trade-off decisions. * Quality & Testing: Define and evolve testing pipelines for non-deterministic flows (Generative AI), ensuring accuracy in benefits and eligibility responses. * Technical Mentorship: Support the growth of mid-level and junior engineers through code reviews, pair programming, and knowledge sharing. * Cross-functional Collaboration: Act as the technical reference in discussions with Product Managers, technical leadership, and QA teams, translating business goals into architectural decisions. Requirements * Professional Experience: 5 to 8 years of experience in Software Engineering, with at least 1 year focused on Artificial Intelligence / Machine Learning projects, including experience leading projects or technical teams. * Programming Languages: Python/Javascript/React and solid experience in API development (FastAPI, Flask, or similar), with strong attention to design best practices and performance. * Generative AI & LLMs: Solid experience building applications using LLMs (OpenAI, Anthropic, Llama, etc.), advanced prompt engineering, RAG (Retrieval-Augmented Generation) architectures, vector databases, and embeddings, including design trade-off decisions (chunking, retrieval strategies). * AI Agents: Experience building or integrating AI agents using orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar. * Cloud Ecosystem (AWS): Strong experience developing cloud-native solutions, preferably within the AWS ecosystem (AWS Bedrock, Lambda, API Gateway, DynamoDB), with the ability to make architectural decisions around cost, performance, and scalability. * Best Practices & MLOps: Solid experience with version control (Git), CI/CD pipelines, and automated testing applied to Machine Learning systems (MLOps), including monitoring and observability of models in production. * Architectural Vision: Ability to evaluate and propose end-to-end architectures for AI solutions, considering security, scalability, cost, and maintainability. Nice-to-Haves * Anthropic certification (e.g., Claude/API certifications) is a plus. * Experience with multi-agent orchestration frameworks such as LangGraph, CrewAI, AutoGen, or similar. * Experience with AI-assisted modernization and legacy migration strategies. * Experience in the healthcare sector (Healthtech), with an understanding of health plan workflows, claims, and medical data protection. * Experience with Kubernetes, containers, and infrastructure automation. * Prior experience mentoring or providing technical leadership to other engineers.
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Sinais de relevancia
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