Devops Engineer (AI)

TL;DR

DevOps Engineer (AI): Designing, deploying, and managing cloud infrastructure on AWS, optimized for AI and ML workloads with an accent on high computational demands and scalability. Focus on automating model training, testing, deployment, and monitoring workflows, ensuring the reliability and high availability of AI-powered applications in production.

Location: Latin America, fully remote

Company

hirify.global helps U.S. companies build and scale world-class AI, ML, and Data teams, powered by the top 1% of LATAM talent.

What you will do

• Design, deploy, and manage cloud infrastructure on AWS, optimized for AI and ML workloads.
• Build, maintain, and optimize CI/CD pipelines tailored for AI/ML and GenAI applications.
• Automate model training, testing, deployment, and monitoring workflows.
• Implement monitoring and observability systems to track model performance, data drift, logs, and system uptime.
• Collaborate with data scientists, ML engineers, and backend developers to ensure secure and smooth deployment of AI services.
• Apply an SRE mindset to improve system resilience, operational excellence, and long-term maintainability.

Requirements

• 5+ years of DevOps experience, with at least 1 year of MLOps and software engineering exposure.
• Strong experience designing and operating systems on AWS (experience with GCP or Azure is a plus).
• Hands-on experience with Docker and Kubernetes in production environments.
• Proven use of Infrastructure as Code tools such as Terraform (Ansible a plus).
• Strong scripting and automation skills using Python and/or Go, plus shell scripting.
• Bachelor’s degree in computer science, engineering, mathematics, statistics, or a related technical field (or equivalent experience).

Nice to have

• Familiarity with vector databases and data-intensive systems.
• Exposure to MLOps tools such as MLflow, Kubeflow, or DVC.

Culture & Benefits

• Ownership through equity participation.
• Annual company retreat.
• Education bonus for continuous learning.
• Company-wide winter break.
• Paid time off.
• Optional in-person events and meetups.