Cloud & AI Engineer – MLOps

Job not on LinkedIn

🕒 February 27

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 41%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Grupo GBI

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤝 B2B

📚 Education

B2B • Education

Grupo GBI is a global event and conference organizer specializing in the coordination and development of high‑level, multisector congresses and executive gatherings across Latin America. The company curates expert speakers and delivers premium in-person events—often at luxury venues—designed to facilitate networking, benchmarking, and professional learning for senior executives and corporate clients. Grupo GBI emphasizes ethical standards, professionalism, and tailored event production services for B2B audiences.

📋 Description

• Design, implement, and maintain cloud environments capable of supporting AI workloads in a scalable and resilient manner • Develop and maintain continuous integration and continuous delivery pipelines for model and application training, versioning, and deployment • Develop and integrate Artificial Intelligence solutions into the company’s ecosystem • Build data pipelines that ensure the quality, availability, and governance of the information used by models • Translate complex requirements into functional architectures while following security, performance, and cost best practices

🎯 Requirements

• Degree in Engineering (Software, Computer, Data, or related fields) or equivalent professional experience • Solid experience with at least one major cloud provider (AWS, Azure, or GCP) • Conceptual understanding of working in multi-cloud environments • Experience with AI frameworks and/or LLMs • Experience integrating via APIs and deploying models to production • Hands-on experience with Docker, Kubernetes, and Infrastructure as Code tools (Terraform, Ansible, or similar) • Proficiency in Python (required) • Knowledge of microservices-based architectures • Certifications in Cloud Computing, Data Engineering, or related fields are a plus, but not required