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Lead AI Engineer

Georgiatek Systems Inc.

São Bernardo do Campo

Presencial

BRL 120.000 - 160.000

Tempo integral

Há 25 dias

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Resumo da oferta

A tech company in Brazil is seeking experienced Lead AI Engineers to design scalable AI solutions. Candidates should have a strong background in Generative AI, RAG architectures, and experience with GCP. Responsibilities include leading engineering initiatives, collaborating with cross-functional teams, and mentoring junior engineers. A Bachelor's or Master’s degree in a relevant field is required. This position offers remote or hybrid work arrangements.

Qualificações

  • 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.

Responsabilidades

  • Lead the design and development of scalable ML models and RAG-based solutions.
  • Build end-to-end AI/ML pipelines using GCP tools.
  • Mentor junior engineers and contribute to AI engineering standards.

Conhecimentos

Generative AI
RAG architectures
Large Language Models (LLMs)
Google Cloud Platform (GCP)
Python
MLOps best practices
AI engineering standards
TensorFlow
PyTorch
Scikit-learn

Formação académica

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field

Ferramentas

Vertex AI
Gemini
Vector Search
LangChain
LangGraph
Google ADK
CrewAI
Kubernetes
Docker
Descrição da oferta de emprego

Lead AI Engineer (3 Positions)

Location : Brazil (Remote / Hybrid based on project needs)

Role Overview

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.

Key Responsibilities
  • 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.
Required Skills & Experience

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.

Preferred Skills (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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