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Lead AI Engineer
Job summary
A leading technology firm is seeking a skilled Lead AI Engineer to design and deploy scalable AI solutions. Based in Brazil, this role involves leadership in AI engineering, collaborating with teams, and implementing MLOps best practices. Candidates should have over 6 years of experience in AI/ML and a strong proficiency in the Google Cloud Platform. This position offers a hybrid work arrangement based on project needs.
Qualifications
- 6+ years of professional experience in AI/ML engineering, including leadership responsibilities.
- Strong hands-on experience with Generative AI and RAG pipelines.
- Experience deploying ML models into production using CI/CD and MLOps.
Responsibilities
- Lead the design and development of scalable ML models and solutions.
- Build end-to-end AI/ML pipelines using GCP tools.
- Partner with data engineers and product stakeholders to integrate AI at scale.
Skills
Education
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).
- 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.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.