Will AI replace a MPLS Engineer?
AI risk 62/100Opportunity 82/100Future demand 58/100
How AI is affecting this role
- ›Instead of manually typing 200 lines of configuration for a new L3VPN, the engineer uses a prompt like 'Create an IOS-XR config for a VRF with import/export RT 65000:100' and pastes the verified output directly.
- ›An AIOps agent notices a recurring micro-burst on a core link and automatically recommends a change to the RSVP-TE bandwidth reservation, which the engineer approves with one click.
- ›During an outage, an AI tool correlates syslog errors from three different routers and pinpoints a mismatched MTU setting on a sub-interface, reducing MTTR from 2 hours to 15 minutes.
Ways to survive
- ›Specialize in physical layer interconnects and last-mile connectivity which AI cannot physically fix.
- ›Master the art of auditing AI output to prevent configuration hallucinations that could bring down the network.
Ways to get ahead with AI
- ›Build a custom internal chatbot using LangChain that allows junior NOC staff to query network status (e.g., 'Show BGP status for Site A') via natural language, automating tier-1 support.
How ONROL helps
We will teach you Python libraries specifically for network automation (Netmiko/Nornir), how to use LLMs to generate and debug Ansible playbooks, and how to integrate AIOps tools into your existing MPLS infrastructure.
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