DevOps Tech Lead for AI Infrastructure

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 qualityMonitor system performance, troubleshoot issues, and ensure high uptime and reliabilityAutomate provisioning, configuration management, and monitoring using tools like Terraform, Ansible, or similarCollaborate with software engineers to understand and support their infrastructure needsDefine and enforce best practices for DevOps, infrastructure as code, security, and observabilityLead 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 lifecycleRequired Qualifications:5+ years of experience in DevOps, Site Reliability Engineering (SRE), or a similar roleStrong 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 administrationExcellent problem-solving, communication, and collaboration skillsExperience with monitoring and observability tools (Prometheus, Grafana, ELK,)Exposure to zero-downtime deployments, blue-green deployments, and canary releasesProficiency with Atlassian tools ( Bitbucket, Jira, Confluence )Familiarity with code quality analysis tools ( linters, static analysis, etc )Strong Git skillsFamiliarity with AI-assisted development tools ( Github Copilot, Curser, Windsurf, etc )Experience deploying and maintaining machine learning modelsExperience integrating LLM workflows, vector search enginesTeam player, fast self-learning individual, and service-oriented attitudeEducation:Bachelor’s degree in computer science, Engineering, or a related field.