Senior Cloud and DevOps Engineer (AI/ML)

TL;DR

Senior Cloud and DevOps Engineer (AI/ML): Designing, optimizing, and securing scalable cloud platforms for AI model training and deployment with an accent on AWS infrastructure management, CI/CD pipelines, and cost control. Focus on troubleshooting incidents, ensuring zero-downtime deployments, and collaborating with AI Ops teams for platform performance and reliability.

Location: Hybrid work model based in Barcelona, Spain, with remote work possibilities.

Company

hirify.global, now part of EPAM Systems, is a Digital Accelerator with over 20 years of experience, fostering a multicultural, startup-minded culture.

What you will do

• Manage cloud infrastructure and optimize costs, particularly in AWS environments using Terraform and Python.
• Design, develop, and maintain CI/CD pipelines and infrastructure for AI model training and deployment.
• Ensure platform scalability, efficient resource utilization, high availability, and resilience in cloud architectures.
• Conduct technical research, analyze findings, and propose optimized architectural solutions.
• Troubleshoot incidents and guarantee smooth, zero-downtime deployments.
• Collaborate closely with AI Ops and technical teams to ensure platform performance, stability, and reliability.

Requirements

• Minimum of 7 years of professional experience in similar roles (Cloud Engineer, DevOps Engineer, MLOps Engineer, or related positions).
• Advanced hands-on experience with AWS infrastructure management, networking, security, and cost optimization.
• Strong expertise in Terraform for Infrastructure as Code (IaC).
• Solid experience using Python for automation and scripting.
• Proven experience designing and maintaining CI/CD pipelines in production environments.
• Experience managing infrastructure for machine learning model training and deployment.
• Advanced English level, both spoken and written.

Nice to have

• Experience with microservices-based architectures and containerization (Docker, Kubernetes).
• Knowledge of observability practices (monitoring, logging, alerting).
• Experience with cost governance and optimization strategies in complex cloud environments.
• Familiarity with MLOps practices and the end-to-end lifecycle of ML models in production.
• AWS or DevOps/MLOps-related certifications.

Culture & Benefits

• Permanent contract with a competitive salary.
• Flexible work model and remote work possibilities.
• Personalized career plan and continuous training (certifications, English).
• Participation in stable, high-technical-impact projects.
• Flexible working hours with a strong focus on work-life balance.
• Social benefits tailored to your needs.