**Senior AI Engineering Specialist**

Há 2 dias


Curitiba, Brasil beBeeLead Tempo inteiro

**Job Summary:** We are seeking highly skilled AI engineers to design, develop and deploy scalable AI and machine learning solutions across enterprise systems. We are looking for professionals with experience in leading AI/ML engineering teams. Strong leadership skills and hands-on experience with Generative AI and RAG pipelines is a must. Key Responsibilities: Design and develop scalable ML models, Generative AI and RAG-based solutions. Build end-to-end AI/ML pipelines using GCP tools: Vertex AI, Gemini, Vector Search and Managed Notebooks. Develop intelligent agents and orchestration using LangChain, LangGraph, Google ADK and CrewAI. Build, fine-tune and deploy custom LLMs and multimodal AI models. Own technical architecture, solution design, performance optimization and deployment strategies. Partner with data engineers, cloud teams and product stakeholders to integrate AI at scale. Implement MLOps best practices for versioning, monitoring, retraining and governance. Mentor junior engineers and contribute to AI engineering standards and frameworks. Requirements: 6+ years of professional experience in AI/ML engineering including leadership responsibilities. Strong hands-on experience with Generative AI and RAG pipelines. Proficiency in Python and ML frameworks TensorFlow, PyTorch and Scikit-learn. Deep expertise in the GCP AI/ML stack including Vertex AI, Gemini, Vector Search and AI Studio / AI APIs. Strong experience with agent-oriented frameworks LangChain, LangGraph, CrewAI and Google ADK. Experience deploying ML models into production using CI/CD and MLOps. Strong understanding of APIs data engineering fundamentals cloud-native deployment and microservices. Excellent communication and ability to lead technical discussions with global teams. Nice to Have: Experience with multi-agent systems and advanced tool orchestration. Knowledge of Kubernetes Docker and cloud-native architectures. Understanding of AI security compliance and responsible AI frameworks. Experience working in global distributed engineering teams. Education: Bachelor's or Master's degree in Computer Science Data Science Engineering or related field.



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