Lead Infrastructure Engineer- Network Planning
On-site · Seattle, Washington, United States
Job Summary
Lead role responsible for strategic evaluation of network technologies and topology standardization (LAN/WAN/DC/Cloud connectivity) to optimize performance, scalability, availability, and operational supportability. Own requirements definition for network planning/tools, translate business outcomes into epics/features, partner with software teams to roadmap tooling, and establish network performance metrics/KPIs with reporting cadences. Analyze performance and capacity data to identify trends and bottlenecks, drive optimization initiatives, build business cases for optimization programs, ensure audit/risk/compliance readiness, and coordinate with regional carriers/service providers to align standards and interoperability. Leverage enterprise AI capabilities to accelerate infrastructure analysis, option evaluation, and design documentation while validating outputs and maintaining data sensitivity and security considerations.
Required Qualifications
- Formal training or certification on network planning and infrastructure engineering concepts
- 5+ years applied experience in network planning/infrastructure engineering
- Deep understanding of network technologies, topologies, and transport protocols
- Experience collaborating with regional carriers or service providers on network solutions
- Proven ability to lead technical initiatives and influence engineering decisions
- Experience in developing and implementing network performance metrics
- Demonstrated ability to define requirements for software tools and collaborate with development teams
- Proven track record of driving performance improvement and design optimization initiatives
- Familiarity with audit, risk, and compliance processes and documentation
- Strong analytical, documentation, and communication skills
- Experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity
- Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations
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