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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer Senior (AI RAG/Javascript/React) - **Company:** CI&T, Inc. - **Location:** Campinas, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Cloud Computing, Code Generation, Code Review, Information Leak Prevention, Data Security, Amazon DynamoDB, Python (Programming Language), Machine Learning, Language Modeling, Pair Programming, Cloud Services, Software Engineering, Systems Integration, ReactJS, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Git, Fastapi, Kubernetes, Infrastructure Automation Frameworks, Machine Learning Operations, Functional Programming, Api Design, Api Gateway, Code Restructuring, Software Version Control - **Published:** August 26, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pfe0iphqdk ## About the Role * 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. ## Description 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. ## Related Videos - [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Engineering Mindset in the Age of AI - Gunnar Grosch, AWS](https://www.wearedevelopers.com/videos/1735-engineering-mindset-in-the-age-of-ai-gunnar-grosch-aws) - [Building and Deploying Multi-Agent Systems with ADK and Vertex AI](https://www.wearedevelopers.com/videos/1918-building-and-deploying-multi-agent-systems-with-adk-and-vertex-ai) - [On a Secret Mission: Developing AI Agents](https://www.wearedevelopers.com/videos/1510-on-a-secret-mission-developing-ai-agents) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)