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Monitor and troubleshoot IP and transmission networks, respond to alarms and outages, resolve incidents, coordinate with providers and internal teams, track SLAs, document resolutions, prepare root cause analyses, and support planned maintenance. The role also contributes to NOC monitoring tools, process improvements, and structured communication during major incidents.

Monitor and troubleshoot IP and transmission networks, investigate alarms and outages, resolve incidents, coordinate with providers and internal teams, track SLAs, and lead incident restoration. The engineer documents incidents, prepares root cause and outage reports, supports planned maintenance, maintains stakeholder communication during major incidents, and improves NOC monitoring tools and processes.

Monitor and troubleshoot IP and transmission networks, investigate alarms and outages, resolve incidents, coordinate with providers and internal teams, track SLAs, document resolutions, prepare root cause analyses, and improve NOC monitoring tools and processes.

Design, prototype, and build AI-powered solutions and internal tools. Evaluate and integrate AI services, develop agents and MCP integrations, build backend services with Python and C#/.NET, create React/TypeScript UIs, and integrate APIs, webhooks, OAuth, databases, cloud platforms, and CI/CD. Rapidly validate technical concepts and collaborate with engineering and business stakeholders to deliver scalable prototypes and production-ready solutions.

Monitor and troubleshoot IP and transmission networks (including xWDM), handle alarms and incidents, resolve first-line issues, coordinate with vendors and providers, document incidents, track SLAs, prepare RCA reports, and improve NOC tools and processes.

Develop and maintain applications using Python, focusing on integrating AI/LLM services with AWS or Azure. Collaborate with teams, implement ML models, and optimize applications for performance.

Design and build production-grade AI applications and services in Python, integrating LLMs with backend APIs and enterprise systems, implementing evaluation frameworks, observability, CI/CD, and reusable components to ensure reliable, testable, and scalable AI features.