Infrastructure Engineer III

• Applies technical knowledge and problem-solving methodologies to projects of moderate scope with a focus on improving the data and systems running at scale and ensures end to end monitoring of infrastructure and applications
• Uses enterprise-authorized AI capabilities within the work environment to accelerate monitoring and capacity analysis and documentation validating outputs and handling operational data according to sensitivity and security requirements
• Resolves most nuances and determines appropriate escalation path
• Executes conventional approaches to build or break down technical problems while considering upstream and downstream data and systems or technical applications
• Drives the daily activities supporting the standard capacity process applications
• Partners with application and infrastructure teams to identify potential capacity risks and govern remediation statuses
• Be accountable for making significant decisions for a project consisting of multiple technologies and applications
• Applies reuse-first AI-assisted approaches to identify recurring capacity risks and improve remediation workflows ensuring changes are validated and aligned to resiliency and security expectations

Required qualifications capabilities and skills

• Formal training or certification on infrastructure engineering concepts and 3 years applied experience
• 2 years of network operations experience
• Operating knowledge of one or more areas of infrastructure engineering such as software defined networks / zero touch provisioning SD-WAN fabric switching Wi-Fi and network security technologies and practices.
• Proficient in specific network infrastructure technology and programming languages (e.g. Python Ansible etc.)
• Strong knowledge of one or more infrastructure disciplines such as hardware networking terminology databases storage engineering deployment practices integration automation scaling resilience and performance assessments
• Demonstrated 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.
• Knowledge of cloud infrastructure and multiple cloud technologies with the ability to operate in and migrate across public and private clouds
• Drives to develop infrastructure engineering knowledge of additional domains data fluency and automation knowledge