Senior Network Automation Engineer

About the role

The Senior Network Automation Engineer is responsible for building and maintaining automation, AI, and machine learning capabilities that enable intelligent network event handling, incident self-healing, predictive insights, and AI-assisted troubleshooting. This role focuses on developing backend services and workflows that analyze network signals, correlate events, and trigger automated diagnostics or remediation actions. This is a hands-on, software-centric role combining network engineering, applied AI/ML, and MLOps.

Responsibilities

• Design and develop network automation services for event correlation, intelligent troubleshooting, and automated remediation.
• Build automation that supports self-healing use cases, such as automated checks and safe remediation actions for recurrent network issues.
• Develop backend automation services using Python and Django, with supporting data stores like Redis for state management.
• Integrate automation services with monitoring, telemetry, and alerting systems to consume events and metrics.
• Partner with Network Operations teams to identify repeatable operational patterns suitable for automation.
• Ensure automation workflows include guardrails, validation, and rollback logic for safe use in production environments.
• Design and productionize machine learning solutions for anomaly detection, event correlation, and predictive maintenance.
• Develop AI-assisted troubleshooting capabilities using large language models and retrieval-augmented generation.
• Build and maintain MLOps pipelines for model validation, deployment, monitoring, and retraining.
• Create APIs and reusable services that integrate AI/ML inference with IT service-management platforms.

Requirements

• Education: A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field is required.
• Experience: This position requires 8–12 years of experience in network engineering, network operations, automation, telemetry, monitoring, data engineering, or applied analytics. This must include demonstrated experience delivering AI/ML-enabled solutions into production.

Skills

• Strong software development experience in Python, including experience with REST APIs, message queues, or workflow engines.
• Experience building