Security-Jobs in Brasilien
Sr. Manager Key Accounts - Protein Ingredients
Bunge Iberica SA
Lead AI Engineer
Georgiatek Systems Inc.
Entdecke mehr Stellenangebote als bei herkömmlichen Stellenportalen. Jetzt mehr Stellenangebote entdeckenGlobal CRM Sustain & Operations Lead
Otis College of Art and Design
Vernetze dich mit Headhuntern um dich auf ähnliche Jobs zu bewerbenAutomation Anywhere Senior RPA Developer
Practia Brasil
Senior Quality Assurance Automation Engineer
Turnkey Tech Staffing
Security Operations Center Analyst
Ust España & Latam
Lead Ai Engineer
Zusammenfassung
A leading technology solutions provider is seeking a skilled Lead AI Engineer in Brazil to design and deploy scalable AI solutions. The ideal candidate will have 6+ years of AI/ML experience and strong expertise in Generative AI, GCP, and leadership skills. This position offers remote/hybrid work options. Join a team driving innovation in AI and automation.
Qualifikationen
- 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.
Aufgaben
- Lead the design and development of scalable ML models.
- Build end-to-end AI / ML pipelines using GCP tools.
- Mentor junior engineers and contribute to AI engineering standards.
Kenntnisse
Ausbildung
Tools
Lead AI Engineer (3 Positions) Location : Brazil (Remote / Hybrid based on project needs)
We are seeking highly skilled Lead AI Engineers based in Brazil to design, develop, and deploy scalable AI and machine learning solutions across enterprise systems. The ideal candidates will have strong expertise in Generative AI , RAG architectures , LLMs , and hands‑on experience with the Google 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.
- Lead the design and development of 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.
- 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, Scikit‑learn).
- Deep expertise in the GCP AI / ML stack , including Vertex AI, Gemini, Vector Search, AI Studio / AI APIs.
- Strong experience with agent‑oriented frameworks : LangChain, LangGraph, CrewAI, 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.
- 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.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
* Der Gehaltsbenchmark wird auf Basis der Zielgehälter bei führenden Unternehmen in der jeweiligen Branche ermittelt und dient Premium-Nutzer:innen als Richtlinie zur Bewertung offener Positionen und als Orientierungshilfe bei Gehaltsverhandlungen. Der Gehaltsbenchmark wird nicht direkt vom Unternehmen angegeben. Er kann deutlich über bzw. unter diesem Wert liegen.