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 Master 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.
- Experience with Docker, Kubernetes, and containerized AI workloads.
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.
- 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.
Skills Required
- Advanced or fluent English at C1 level or higher
- Experience working with international clients and global teams
- Hands-on experience with automation, Generative AI, LLMs, RAG, and agent-based architectures
- Proficiency in Python and software engineering best practices
- Experience designing secure, scalable, production-ready AI systems
- Understanding of AI model evaluation, deployment, observability, and operational reliability
- Experience with agent execution pipelines, CI/CD integrations, backend AI workflows, and automated orchestration
- Knowledge of prompt engineering, context management, hallucination mitigation, and knowledge freshness strategies
- Ability to work autonomously in complex, fast-paced, and ambiguous environments
- Experience with Docker, Kubernetes, and containerized AI workloads
- Experience deploying Generative AI solutions using Azure, AWS, or GCP
- Familiarity with Databricks, Vertex AI, Azure OpenAI, Amazon Bedrock, or similar enterprise AI platforms
- 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
What We Do
CI&T is your end-to-end digital transformation partner. As a digital native, we bring a 27-year track record of accelerating business impact through complete and scalable digital solutions. With a global presence of 6,000+ professionals in strategy, research, data science, design and engineering, we unlock top-line growth, improve customer experience and drive operational efficiency.
