DevOps Tech Lead for AI Infrastructure
Kfar Saba
301-Engineering – 301-Engineering /
Full Time /
Hybrid
Parallel Wireless is reimagining mobile networks with innovative, energy-efficient Open RAN solutions. Join us as we lead the future of telecommunications, driving innovation through green and sustainable networks. Learn more about our mission, vision and values.
We are looking for a highly skilled DevOps Engineer to lead AI initiatives within the engineering group by leveraging AI-driven tools and integrating them into the CI/CD pipeline to enhance code quality and optimize the software development lifecycle.
Responsibilities:
- Design, implement, and maintain scalable, secure, and highly available cloud infrastructure (e.g., AWS, Azure, GCP)
- Develop and optimize CI/CD pipelines to improve deployment speed and quality
- Monitor system performance, troubleshoot issues, and ensure high uptime and reliability
- Automate provisioning, configuration management, and monitoring using tools like Terraform, Ansible, or similar
- Collaborate with software engineers to understand and support their infrastructure needs
- Define and enforce best practices for DevOps, infrastructure as code, security, and observability
Required Qualifications:
- 5+ years of experience in DevOps, Site Reliability Engineering (SRE), or a similar role
- Strong hands-on experience with cloud platforms (AWS, GCP, or Azure)
- Proficiency with Infrastructure as Code tools (Terraform, CloudFormation)
- Experience with configuration management tools
- Deep knowledge of CI/CD tools
- Strong scripting skills (Bash, Python, or Go)
- Proficiency with containers and orchestration (Docker, Kubernetes, Helm)
- Solid understanding of networking, security best practices, and Linux system administration
- Excellent problem-solving, communication, and collaboration skills
- Experience with monitoring and observability tools (Prometheus, Grafana, ELK,)
- Exposure to zero-downtime deployments, blue-green deployments, and canary releases
- Proficiency with Atlassian tools (Bitbucket, Jira, Confluence)
- Familiarity with code quality analysis tools (linters, static analysis, etc)
- Strong Git skills
- Familiarity with AI-assisted development tools (Github Copilot, Curser, Windsurf, etc)
- Experience deploying and maintaining machine learning models
- Experience integrating LLM workflows, vector search engines
- Team player, fast self-learning individual, and service-oriented attitude
Education:
- Bachelor’s degree in computer science, Engineering, or a related field.
