• Published: February 6, 2021
Job Type
Level of education
Level of Hebrew
Location of job
How many relevant years experience do you require for the role:
3 years


We are building a state of the art AI auto ML that integrate directly to common day to day analytics tools like Google Sheets, Power BI & Tableau

What will you do?

- Play a key role in creating the infrastructure for developing and serving a Saas Product.
- Develop, maintain, and optimize tools for deploying our product in production.
- Maintain, monitor, analyze, and troubleshoot issues in dynamic and complex environments.
- Work with a variety of technologies, methods, platforms, and practices both on cloud and on-premises.
- Own domains end-to-end and be part of our product’s life cycle starting from the design to deployment to a live production system.
- Influence and optimize our SDLC(Software Development Lifecycle)


- +3 years of experience as a Cloud/DevOps engineer.
- +3 years of experience with building & maintaining Node.JS applications
- Hands-on experience designing and building SaaS products
- Vast experience with design, build and manage infrastructure on Azure or AWS.
- Hands-on working with queues (RabbitMQ, ActiveMQ, Kafka)
- Hands-on experience working with Serverless (AWS Lambda/Azure Functions)
- Hands-on experience designing and building CI/CD pipelines
- (SCM / Artifacts repository managers / Deployment tools)
- Hands-on experience writing and managing Infrastructure as code with Terraform or cloud provider IaC.
- Deep understanding of working with docker
- Deep understanding of Kubernetes.
- Deep knowledge about Linux operating systems.
- Deep knowledge about network storage (NFS, CephFS)
- Familiarity with one of the following scripting languages: Bash, Python.


- B.Sc. (or equivalent) in Computer Engineering, Computer Science, or related technical experience.
- Experience with one of the following programming languages: Python, Scala, Go, or equivalent language.
- Hands-On experience working with AWS EKS in production environments.
- Hands-On experience working with Azure cloud environments.
- Familiarity with monitoring/logging tools: ELK stack, Prometheus, FluentD.
- Experience with the development of CLI tools, REST API, SDKs.

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