[Job-29944] AI Engineer Senior (Javascript/React)

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.