DevOps Engineer - Security

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April 2

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turba

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Artificial Intelligence • Enterprise • SaaS

turba is transforming AI by optimizing AI/ML infrastructures for faster and more efficient model deployment. Their innovative solutions enhance performance, reduce costs, and ensure reliable, scalable AI operations for businesses. turba is dedicated to pushing the boundaries in AI and ML, supporting an engineering-driven culture and providing tailored solutions that help businesses manage their AI operations effectively, all while ensuring SLA compliance and enabling seamless multicloud deployments.

11 - 50 employees

Founded 2024

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

📋 Description

• Design, build, and maintain robust CI/CD pipelines to support rapid development and deployment cycles • Automate infrastructure provisioning and scaling using tools like Terraform, Kubernetes or Docker • Ensure seamless and reliable operations, always prioritizing the availability and performance of our infrastructure • Implement secure access mechanisms for Turba employees to access Turba infrastructure as well as customer on-premise deployments • Use security best-practices to ensure Turba infrastructure is protected against cyber-attacks • Ensure Turba's IP is protected during CI/CD pipeline operations • Help our customers to access Turba's services in a secure manner • Implement optimizations, drive improvements and stay up to date with new technologies and current developments

🎯 Requirements

• Practical experience as a DevOps Engineer • Proficiency in scripting languages (Python, Bash) • Expertise in CI/CD tools like Jenkins, GitLab CI, or CircleCI • Experience with containerization and orchestration tools (Docker, Kubernetes) • Strong knowledge of cloud platforms (AWS, Azure, GCP) and Infrastructure as Code (Terraform, Ansible/Chef) • Hands-on experience with security tools and technologies (e.g., firewalls, intrusion detection/prevention systems, VPNs, SIEM) • Knowledge of DevSecOps, MLOps als well as OpenStack is a plus • Knowledge of ML model lifecycle management, data pipelines, or AI frameworks (TensorFlow, PyTorch) is a plus

🏖️ Benefits

• Competitive salary and benefits package • Flexible working hours and remote options • Flat hierarchies, short decision-making paths, and plenty of room for your ideas • Collaborative and innovative work environment • The opportunity to be directly involved in building a startup