DevOps Engineer - 5467

Senior DevOps Engineer

A leading international high-tech company specializing in AI solutions is seeking an experienced and innovative Senior DevOps Engineer with strong capabilities in large-scale cloud environments. The role includes responsibility for building advanced automation infrastructures, managing extensive cloud environments, and continuously improving development and deployment processes that support resource-intensive and data-driven AI systems.

Core Responsibilities:

• Designing, building, and maintaining large-scale CI/CD infrastructures for algorithm, model, and AI system development teams.
• Managing IaC-based infrastructure using Terraform as part of automated provisioning processes.
• Ongoing work with large cloud environments optimized for model training, system execution, and intelligent deployments, including load management, auto-scaling, and high availability capabilities.
• Supporting development, data, and MLOps teams to enhance performance, shorten development cycles, and ensure system stability.
• Continuous improvement of security processes, monitoring, and alerting in complex production environments.
• Leading cross-organizational DevOps projects, including designing cloud architectures for resource-intensive AI applications.

Mandatory Requirements:

• At least 8 years of experience in DevOps, specializing in cloud infrastructure and advanced automation.
• Deep knowledge of IaC tools with full proficiency in Terraform.
• Experience managing large-scale cloud infrastructures, with strong understanding of networking, security, scalability, and observability.
• Proven experience working with Linux environments and scripting in Bash or Python.
• Significant experience implementing CI/CD using modern industry-standard tools.
• Hands-on experience with Azure and building complex cloud infrastructures in this environment.
• Experience in MLOps, containers, and Kubernetes, including managing model execution environments.

Strong Advantage:

• Background working with data-intensive AI systems, Big Data infrastructures, or Machine Learning pipelines.