Summary: Seeking an AI/ML Engineer to develop and operationalize GenAI solutions, facilitate the Data & AI Platform, and contribute to advanced AI/ML initiatives for Latin America's leading airline. Highlights: 1. Contribute to cutting-edge GenAI solutions for a leading airline 2. Combine ML/AI engineering with strong software and cloud skills 3. Collaborate with cross-functional teams on high engineering standards Client: Our client is the leading airline in Latin America, operating the largest network of destinations, frequencies, and fleet in the region. The company is driving innovation through advanced AI/ML initiatives, with a strong focus on next\-generation GenAI solutions. Project overview: You will join a strategic initiative within the Emantto domain, contributing to the acceleration of LATAM’s AI portfolio across multiple touchpoints. The role combines ML/AI engineering with strong software, cloud, and infrastructure skills. You will build and operate GenAI\-driven data products, support domain teams, and act as a facilitator of LATAM’s Data \& AI Platform. Position overview: We are looking for an AI/ML Engineer with solid knowledge in Cloud, IaC, CI/CD, and SWE best practices, focused on designing, building, and operationalizing GenAI\-based solutions. * Responsibilities: Develop and deliver data products and AI/GenAI solutions within domain teams. * Act as a facilitator of LATAM’s Data \& AI Platform, enabling adoption and accelerating delivery across squads. * Build, deploy, and operate GenAI/ML models in scalable, production\-ready environments. * Manage infrastructure topics for environments and AI/ML products, including observability, performance, and reliability. * Contribute to CI/CD pipelines, IaC practices, and platform automation. * Collaborate with cross\-functional teams (SWE, Data, MLOps, DevOps) to ensure high engineering standards. * Support experimentation frameworks and internal tools for GenAI model development and evaluation. * Requirements: Experience with GCP (or a similar cloud provider such as AWS/Azure). * Experience with Terraform or other IaC tools. * Strong knowledge of Python. * Backend engineering experience (APIs, services) and GenAI OR ML/MLOps experience (Airflow, MLflow, pipelines, monitoring. * Solid understanding of CI/CD, containerization (Docker), and SWE best practices. * Familiarity with model deployment, model serving, and operating ML/AI systems in production. Nice to have: Experience with observability, incident response, or platform operations.