
5001 - 10000 employees
Founded 1995
đ¤ Artificial Intelligence
âď¸ SaaS
đ° $5.5M Venture Round on 2014-04
Artificial Intelligence ⢠Cloud Services ⢠SaaS
CI&T is a global tech transformation specialist focusing on helping organizations navigate their technology journey. With services spanning from application modernization and cloud solutions to AI-driven data analytics and customer experience, CI&T empowers businesses to accelerate their growth and maximize operational efficiency. The company emphasizes digital product design, strategy consulting, and immersive experiences, ensuring a robust support system for enterprises in various industries.
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5001 - 10000 employees
Founded 1995
đ¤ Artificial Intelligence
âď¸ SaaS
đ° $5.5M Venture Round on 2014-04
Artificial Intelligence ⢠Cloud Services ⢠SaaS
CI&T is a global tech transformation specialist focusing on helping organizations navigate their technology journey. With services spanning from application modernization and cloud solutions to AI-driven data analytics and customer experience, CI&T empowers businesses to accelerate their growth and maximize operational efficiency. The company emphasizes digital product design, strategy consulting, and immersive experiences, ensuring a robust support system for enterprises in various industries.
⢠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 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.
⢠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: Proven 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.
⢠Health and dental insurance ⢠Meal and food allowance ⢠Childcare assistance ⢠Extended paternity leave ⢠Partnerships 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 responsible parenting course ⢠Partnerships with online learning platforms ⢠Language learning platform ⢠And many more!
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