Job responsibilities

• Applies technical expertise and problem-solving methodologies to projects of moderate scope
• Drives a workstream or project consisting of one or more infrastructure engineering technologies
• Works with other platforms to architect and implement changes required to resolve issues and modernize the organization and its technology processes
• Executes creative solutions for the design, development, and technical troubleshooting for problems of moderate complexity
• Strongly considers upstream/downstream data and systems or technical implications and advises on mitigation actions
• Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.

• Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations.

   

• Manages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and product supportability requirements
• Partners with engineering and product teams to ensure remediation/permanent closure of issues and to identify trending issues to drive product improvement
• Demonstrates a high aptitude for both learning and teaching as product teams are continually releasing new features and products
• Provides (follow the sun) 24/7 on call support through a distributed team spanning multiple time zones.

Required qualifications, capabilities, and skills

• Formal training or certification on Infrastructure engineering concepts and 5+ years applied experience
• Deep knowledge of one or more areas of infrastructure engineering such as hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience, or performance assessments
• Deep knowledge of one specific infrastructure technology and scripting languages (e.g., Scripting, Python, etc.) and AWS certification(s)
• Drives to continue to develop technical and cross-functional knowledge outside of the product
• Deep knowledge of cloud infrastructure and multiple cloud technologies with the ability to operate in and migrate across public and private clouds. 
• 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.
• A drive to continue to develop technical and cross-functional knowledge
• Familiarity with working in a large distributed system across a range of technologies including compute, databases, messaging, observability, and telemetry
• Knowledge of incident, change, and problem management processes and the controls that govern them

• Understanding of data-driven decision making

   

• Kubernetes, Azure, GCP, or Terraform certifications
• Comfortable exploring AI tools to speed up troubleshooting and documentation, with proper verification and data protection.