Senior network engineer reviewing enterprise logs, packets, and wireless incidents for AI-driven autonomous networking systems.
Structuring production network data into machine-learning training inputs and annotations.
Responsibilities
Review production networking data including logs, configurations, telemetry, and event streams
Label and classify network behaviours, incidents, anomalies, and recurring failure patterns
Identify relationships between symptoms, network events, and root causes
Produce structured annotations for AI and machine learning workflows
Troubleshoot complex enterprise networking incidents and reconstruct troubleshooting workflows
Perform packet-level analysis using Wireshark, tcpdump, SPAN captures, and similar tools
Diagnose enterprise Wi-Fi, authentication, roaming, interference, coverage, and wireless-performance issues
Evaluate incident-response and root-cause-analysis workflows
Identify gaps or inconsistencies in operational records and troubleshooting sequences
Help define schemas and structures for networking datasets
Translate infrastructure data into machine-learning inputs
Collaborate with technical teams developing autonomous infrastructure capabilities
Requirements
Current or recent experience as a Level 3 / Tier 3 Network Support Engineer, Principal Support Engineer, Senior Network Engineer, or comparable escalation-focused role
Strong experience maintaining existing enterprise network infrastructure in production
Hands-on responsibility for final escalations, incident response, troubleshooting, RCAs, and on-call support
Direct experience supporting end-customer enterprise networks involving switches, wireless access points, and firewalls
Strong enterprise Wi-Fi expertise, including WLAN controllers and wireless troubleshooting
Hands-on knowledge of Cisco WLC, Aruba, Meraki, or comparable enterprise wireless platforms
Strong understanding of 802.1X, RADIUS, and enterprise authentication workflows
Practical packet-analysis experience using Wireshark, tcpdump, SPAN, or similar tools
Ability to interpret logs, configurations, telemetry, and event data from production systems
Interest in transforming infrastructure data into machine-learning training inputs
Strong written English and ability to document technical reasoning clearly
Candidates must be authorised to work in the United States or Canada without sponsorship
Individual contractor engagement only; corp-to-corp and agency billing arrangements are not supported
H1-B and STEM OPT support is unavailable
Benefits
Fully remote
Independent contractor engagement
Approximately 30–40 hours per week
Projects may be extended, shortened, or concluded based on project needs and performance
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