Chief Architect

Há 2 dias

Rio de Janeiro, Rio de Janeiro, Brasil beBeeData Tempo inteiro R$200.000 - R$250.000
Senior Data & AI Engineering Manager Role

The position of Senior Data and AI Engineering Manager is a pivotal role in leading the development and deployment of scalable, secure, and innovative data and AI products aligned with business goals and product vision.

This leadership position involves guiding multidisciplinary teams including data engineers, machine learning engineers, AI specialists, and platform architects. It also entails fostering a culture of technical excellence, collaboration, and continuous learning.

As a Senior Data and AI Engineering Manager, you will play a central role in bringing data and AI product vision to life, building foundational platforms and teams that drive transformation in various sectors.

Key Responsibilities:
  • Develop and execute the overall data and AI strategy, directly supporting business industrial product vision and roadmap.
  • Architect and oversee end-to-end development of data and AI platforms, ensuring scalability, security, and modularity.
  • Lead, mentor, and retain high-performing teams, promoting innovation, ownership, and technical rigor.
  • Implement and enforce best practices for data governance, quality, privacy, compliance, and responsible AI aligned with industry regulations.
  • Cultivate strategic partnerships, evaluate third-party technologies, and lead platform evolution, integrating the latest advances in AI/ML, cloud, and data engineering.
  • Establish and track KPIs to measure the business impact of data and AI solutions.
Requirements:
  • Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related STEM field.
  • Proven experience in technical leadership of end-to-end data, AI, and ML projects, including managing multidisciplinary engineering teams.
  • Hands-on expertise in Python, software engineering, cloud platforms (AWS, Azure, GCP), data architecture, and scalable data pipelines.
  • Familiarity with AI/ML frameworks and tools (Scikit-Learn, TensorFlow, PyTorch, HuggingFace, etc.), MLOps best practices, and platform development.
  • Track record in building robust internal platforms, APIs, and data/ML products with a focus on quality, security, and reliability.
  • Experience implementing governance, privacy, and compliance standards, with a strong commitment to ethical and explainable AI.
  • Strategic planning, project portfolio management, and the ability to influence both technical and non-technical audiences.
  • Excellent communication and stakeholder management skills.
  • Fluent English language skills.

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