לוח משרות דרושים איש DevOps בנתניה

Were reinventing DevOps to help the worlds greatest companies innovate and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if youre willing to do more, your career can take off. And since software plays a central role in everyones lives, youll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust us to manage, accelerate, and secure their software delivery from code to production a concept we call liquid software. Wouldn't it be amazing if you could join us on our journey?

As a DevOps Engineer you will...
Build, own, and improve the developer's our toolbox.
Maintain environments for developers to test and debug their code (e.g., performance, load, functional and scale testing).
Increase development velocity by adopting and integrating new technologies and tools.
Work side-by-side with development teams to improve the CI lifecycle, including test stability, duration, and quality gates.
Design, implement, and maintain scalable CI/CD pipelines using GitHub. Actions, Jenkins and other modern DevOps tools to enable automated, reliable multi-environment deployments.

DRS RADA is a global pioneer of RADAR systems for active military protection, counter-drone applications, critical infrastructure protection, and border surveillance.
Join Our Team as a IT Infrastructure & Cloud Specialist at DRS RADA Technologies!
Key Responsibilities:
Cloud Infrastructure Management: Administer and manage Azure cloud services, including compute, storage, networking, and identity management.
DevOps Integration: Collaborate with development teams to design, implement, and manage continuous integration and continuous delivery (CI/CD) pipelines, leveraging Azure DevOps and automation tools.
Configure, manage, and monitor Data Lakes, Data Warehouses, and big data pipelines.
Cloud Security & Compliance: Implement and manage security controls for cloud infrastructure, applications, and services to ensure the following of security best practices.
Automation: To streamline operational tasks and infrastructure deployment, develop and maintain automation scripts using PowerShell, ARM templates, or Azure DevOps Pipelines , Azure Workflows (Logic Apps)
Monitoring & Optimization: Monitor cloud resources, optimize performance, and ensure cost-effective cloud infrastructure management.
Infrastructure as Code: Implement and manage Infrastructure as Code (IaC) using tools like Terraform or Azure Resource Manager (ARM) templates.
Collaboration: Work closely with developers and other teams to identify opportunities for cloud-based solutions and improve current infrastructure.
Networking & VMware Management: Manage VMware environments and virtualized infrastructure. Oversee networking aspects, including virtual networks, VPNs, and network security, within Azure and on-prem environments.
Identity Management: Administer Active Directory (AD) and Entra ID (Azure Active Directory), ensuring proper integration, security, and synchronization between cloud and on-prem identity services.
Troubleshooting & Support: Provide technical support and troubleshooting for cloud-related issues, ensuring minimal downtime and disruption.
Documentation & Reporting: Maintain clear documentation of cloud infrastructure, automation processes, and configuration
API Management: Implement and manage Azure API Management (APIM) to expose and manage APIs securely and ensure smooth integration between internal and external services.
AI Infrastructure: Manage and optimize the deployment of Azure AI infrastructure services, including Azure Machine Learning and cognitive services, to support data-driven projects and AI-driven solutions.

We are looking for a Azure Devops.

We are seeking a highly skilled and motivated MLOps Engineer to join our team and play a critical role in the deployment, automation, and maintenance of our machine learning infrastructure. You will be responsible for ensuring that our ML models move seamlessly from experimentation to production with stability, security, and scalability in mind. You will work closely with data scientists, machine learning engineers, and DevOps teams to build robust model pipelines, manage infrastructure across on-prem and cloud, and enforce best practices in version control, model deployment, and compliance. Key Responsibilities: · Design, implement, and maintain automated model training pipelines using tools such as MLflow, (Kubeflow, Airflow), or custom orchestrators. · Support reproducibility and consistency across model training environments. · Implement and manage Artifactory. · Establish and maintain model registries to track versions, metadata, and lineage. · Automate model promotion through staging, testing, and production environments. · Build CI/CD pipelines tailored for ML use cases, integrating model training, validation, deployment, and rollback. · Manage and scale infrastructure across cloud platforms (Azure) and on-premise environments · Optimize GPU/CPU resource utilization and cost efficiency. · Implement auto-scaling and load balancing strategies for ML workloads. · Manage version control systems (e.g., Git) and integrate with experiment tracking tools. · Handle storage and retrieval of artifacts (e.g., Docker images, models, datasets) via artifact registries like JFrog Artifactory or AWS ECR.