Lead AI Engineer

Há 3 dias

ribeirão pires, Brasil GeorgiaTEK Systems Inc. Tempo inteiro

Lead AI Engineer (3 Positions) Location:Brazil (Remote / Hybrid based on project needs)Role Overview We are seeking highly skilledLead AI Engineersbased inBrazilto design, develop, and deploy scalable AI and machine learning solutions across enterprise systems. The ideal candidates will have strong expertise inGenerative AI ,RAG architectures ,LLMs , and hands-on experience with theGoogle Cloud Platform (GCP)AI ecosystem. You will lead AI engineering initiatives, collaborate with cross-functional teams, and drive innovation in intelligent automation, personalization, and data-driven decision-making.Key Responsibilities Lead the design and development of scalableML models ,Generative AI , andRAG-basedsolutions. Build end-to-endAI/ML pipelinesusing GCP tools:Vertex AI ,Gemini ,Vector Search , and Managed Notebooks. Develop intelligent agents and orchestration usingLangChain ,LangGraph ,Google ADK , andCrewAI . 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.Required Skills & Experience 6+ years of professional experience inAI/ML engineering , including leadership responsibilities. Strong hands-on experience withGenerative AIandRAG pipelines . Proficiency inPythonand ML frameworks (TensorFlow, PyTorch, Scikit-learn). Deep expertise in theGCP AI/ML stack , including: Vertex AI Gemini Vector Search AI Studio / AI APIs Strong experience withagent-oriented frameworks : LangChain LangGraph CrewAI Google ADK Experience deploying ML models into production usingCI/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.Preferred Skills (Nice to Have) Experience withmulti-agent systemsand advanced tool orchestration. Knowledge ofKubernetes ,Docker , and cloud-native architectures. Understanding ofAI security, compliance, and responsible AIframeworks. 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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