[Job-31014] Senior Software Developer

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. 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 responsible parenting course -Partnerships with online learning platforms -Language learning platform And many more! More details about our benefits here: https://ciandt.com/br/pt-br/carreiras At CI&T, inclusion starts at the first contact. If you are a person with a disability, it is important to present your assessment during the selection process. See which data needs to be included in the report by clicking here.This way, we can ensure the support and accommodations that you deserve. If you do not yet have the assessment, don't worry: we can support you in obtaining it. We have a dedicated Health and Well-being team, inclusion specialists, and affinity groups who will be with you at every stage. Count on us to make this journey side by side. At CI&T, we are looking for a Senior Software Developer to join our global team and help design, build, and scale advanced Generative AI and Agentic AI solutions for enterprise clients. This role is ideal for a professional with deep hands-on experience in Generative AI, LLMs, RAG, and agent-based architectures, combined with strong software engineering, cloud, and production-grade AI platform expertise. You will work on the development of secure, scalable, observable, and reliable AI applications that support complex business workflows and large-scale enterprise environments. Key Responsibilities- Design, develop, and maintain GenAI and Agentic AI applications for production environments.- Build customizable agent solutions using frameworks such as LangChain, DeepAgents, Strands AI, or similar Agent SDKs.- Develop production-grade Python tooling and reusable AI components.- Implement RAG pipelines, external knowledge integrations, memory management, and context orchestration strategies.- Design secure sandboxed execution environments for agent tooling, including permissions, secrets management, network restrictions, and auditability.- Build and maintain MCP (Multi-Cloud Platform) tooling, including authentication, schema design, versioning, retries, and safe execution boundaries.- Implement observability, tracing, logging, and monitoring for prompts, tool calls, model performance, latency, and cost optimization.- Create automated evaluation and testing frameworks for AI agents, including golden datasets, regression tests, hallucination detection, and quality gates.- Design human-in-the-loop approval workflows for sensitive or high-risk operations.- Manage prompt versioning, model routing, fallback strategies, and token/cost optimization for enterprise AI systems.- Collaborate with Data, Analytics, Platform Engineering, and business stakeholders to deliver scalable AI solutions aligned with business goals. Required Qualifications- Advanced / Fluent English (C1 or higher), mandatory.- Experience working with international clients and global teams.- Strong hands-on experience with Automation, Generative AI, LLMs, RAG, and agent-based architectures (E.g.: Claude Code, Codex, Cursor, Windsurf)- Proficiency in Python and software engineering best practices.- Experience designing secure, scalable, and production-ready AI systems.Solid understanding of AI model evaluation, deployment, observability, and operational reliability.- Experience with agent execution pipelines, CI/CD integrations, backend AI workflows, and automated orchestration.- Strong knowledge of prompt engineering, context management, hallucination mitigation, and knowledge freshness strategies.- Ability to work autonomously in complex, fast-paced, and ambiguous environments. Nice to Have- Experience with Azure, AWS, or GCP, especially deploying Generative AI solutions in cloud environments.- Familiarity with Databricks, Vertex AI, Azure OpenAI, Amazon Bedrock, or similar enterprise AI platforms.- Experience with Docker, Kubernetes, and containerized AI workloads.Knowledge of MLOps and AI/ML pipeline automation.- Understanding of AI security, governance, compliance, and data privacy regulations.- Certifications related to Generative AI, Machine Learning, Cloud, or AI Engineering. 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. At CI&T, we are looking for a Senior Software Developer to join our global team and help design, build, and scale advanced Generative AI and Agentic AI solutions for enterprise clients. This role is ideal for a professional with deep hands-on experience in Generative AI, LLMs, RAG, and agent-based architectures, combined with strong software engineering, cloud, and production-grade AI platform expertise. You will work on the development of secure, scalable, observable, and reliable AI applications that support complex business workflows and large-scale enterprise environments. Key Responsibilities- Design, develop, and maintain GenAI and Agentic AI applications for production environments.- Build customizable agent solutions using frameworks such as LangChain, DeepAgents, Strands AI, or similar Agent SDKs.- Develop production-grade Python tooling and reusable AI components.- Implement RAG pipelines, external knowledge integrations, memory management, and context orchestration strategies.- Design secure sandboxed execution environments for agent tooling, including permissions, secrets management, network restrictions, and auditability.- Build and maintain MCP (Multi-Cloud Platform) tooling, including authentication, schema design, versioning, retries, and safe execution boundaries.- Implement observability, tracing, logging, and monitoring for prompts, tool calls, model performance, latency, and cost optimization.- Create automated evaluation and testing frameworks for AI agents, including golden datasets, regression tests, hallucination detection, and quality gates.- Design human-in-the-loop approval workflows for sensitive or high-risk operations.- Manage prompt versioning, model routing, fallback strategies, and token/cost optimization for enterprise AI systems.- Collaborate with Data, Analytics, Platform Engineering, and business stakeholders to deliver scalable AI solutions aligned with business goals. Required Qualifications- Advanced / Fluent English (C1 or higher), mandatory.- Experience working with international clients and global teams.- Strong hands-on experience with Automation, Generative AI, LLMs, RAG, and agent-based architectures (E.g.: Claude Code, Codex, Cursor, Windsurf)- Proficiency in Python and software engineering best practices.- Experience designing secure, scalable, and production-ready AI systems.Solid understanding of AI model evaluation, deployment, observability, and operational reliability.- Experience with agent execution pipelines, CI/CD integrations, backend AI workflows, and automated orchestration.- Strong knowledge of prompt engineering, context management, hallucination mitigation, and knowledge freshness strategies.- Ability to work autonomously in complex, fast-paced, and ambiguous environments. Nice to Have- Experience with Azure, AWS, or GCP, especially deploying Generative AI solutions in cloud environments.- Familiarity with Databricks, Vertex AI, Azure OpenAI, Amazon Bedrock, or similar enterprise AI platforms.- Experience with Docker, Kubernetes, and containerized AI workloads.Knowledge of MLOps and AI/ML pipeline automation.- Understanding of AI security, governance, compliance, and data privacy regulations.- Certifications related to Generative AI, Machine Learning, Cloud, or AI Engineering.