> Markdown version of [/jobs/ext/2241330-master-software-developer-ai-generative](https://www.wearedevelopers.com/jobs/ext/2241330-master-software-developer-ai-generative). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Master Software Developer ( AI Generative) - **Company:** CI&T, Inc. - **Location:** Campinas, United States (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Continuous Integration, Cursor (Graphical User Interface Elements), Memory Management, Python (Programming Language), Key Management, Machine Learning, Regression Testing, Software Construction, Management of Software Versions, Data Logging, Cloud Platform System, Delivery Pipeline, Large Language Models, Prompt Engineering, Model Validation, Multi-Cloud, Generative AI, Backend, AI Platforms, Kubernetes, Machine Learning Operations, Virtual Agents, Automation Anywhere, Docker, Databricks - **Published:** August 26, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pfdzn3hnji ## About the Role 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. ## Description You will work on the development of secure, scalable, observable, and reliable AI applications that support complex business workflows and large-scale enterprise environments., 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. ## Related Videos - [The State of GenAI & Machine Learning in 2025](https://www.wearedevelopers.com/videos/1383-the-state-of-genai-machine-learning-in-2025) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Make it simple, using generative AI to accelerate learning](https://www.wearedevelopers.com/videos/969-make-it-simple-using-generative-ai-to-accelerate-learning) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [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) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care)