DevJobs

DevOps Tech Lead for AI Infrastructure

Overview
Skills
  • Python Python
  • Bash Bash
  • Go Go
  • Elasticsearch Elasticsearch
  • JIRA JIRA
  • Bitbucket Bitbucket
  • Git Git
  • Azure Azure
  • GCP GCP
  • AWS AWS
  • Docker Docker
  • Helm
  • Kubernetes Kubernetes
  • Grafana Grafana
  • Terraform Terraform
  • Confluence
  • CloudFormation
  • Prometheus Prometheus
  • Curser
  • Github Copilot
  • Windsurf
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.
Parallel Wireless