Senior Cloud And Devops Engineer

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.CompanyNEORIS, now part of EPAM Systems, is a Digital Accelerator with over 20 years of experience, fostering a multicultural, startup-minded culture.What you will doManage 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.Troubleshoot incidents and guarantee smooth, zero-downtime deployments.Collaborate closely with AI Ops and technical teams to ensure platform performance, stability, and reliability.RequirementsMinimum 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 haveExperience 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 & BenefitsPermanent 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.#J-*****-Ljbffr

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.CompanyNEORIS, now part of EPAM Systems, is a Digital Accelerator with over 20 years of experience, fostering a multicultural, startup-minded culture.What you will doManage 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.Troubleshoot incidents and guarantee smooth, zero-downtime deployments.Collaborate closely with AI Ops and technical teams to ensure platform performance, stability, and reliability.RequirementsMinimum 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 haveExperience 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 & BenefitsPermanent 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.