Consultant - Automation
2 weeks ago
As a Consultant in Automation domain, you will be responsible for delivering automation use cases enabled by AI and Cloud technologies. In this role, you play a crucial part in building the next-generation autonomous networks. You will develop efficient and scalable automation solutions, you will leverage your technical expertise, problem-solving abilities, and domain knowledge to drive innovation and efficiency.
You have:
- Bachelor's degree in Computer Science, Engineering, or a related field preferred, with 8-10+ years of experience in automation or telecommunications.
- Understanding of telecom network architecture, including Core networks, OSS, and BSS ecosystems, along with industry frameworks like TM Forum Open APIs and eTOM.
- Practical experience in programming and scripting languages such as Python, Go, Java, or Bash, and automation tools like Terraform, Ansible, and Helm.
- Hands-on experience with CI/CD pipelines using Jenkins, GitLab CI, or ArgoCD, as well as containerization (Docker) and orchestration (Kubernetes, OpenShift).
It would be nice if you also had:
- Exposure to agile development methodologies and cross-functional collaboration.
- Experience with real-time monitoring tools (Prometheus, ELK Stack, OpenTelemetry, Grafana) and AI/ML for predictive automation and network optimization is a plus.
- Familiarity with GitOps methodologies and automation best practices for telecom environments.
- Design, develop, test, and deploy automation scripts using languages such as Python, Go, Bash, or YAML.
- Automate the provisioning, configuration, and lifecycle management of network and cloud infrastructure.
- Design and maintain CI/CD pipelines using tools like Jenkins, GitLab CI/CD, ArgoCD, or Tekton.
- Automate continuous integration, testing, deployment, and rollback mechanisms for cloud-native services.
- Implement real-time monitoring, logging, and tracing using tools such as Prometheus, Grafana, ELK, and OpenTelemetry.
- Develop AI/ML-driven observability solutions for predictive analytics and proactive fault resolution, integrating AI/ML models to enable predictive scaling.
- Automate self-healing mechanisms to remediate network and application failures.
- Collaborate with DevOps and Network Engineers to align automation with business goals.
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