Cloud Lead Infrastructure Engineer - Technical Solutions Engineering

• Applies technical expertise and problem-solving methodologies to projects of moderate scope and executes creative solutions for design, development, and technical troubleshooting for problems of moderate complexity
• 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.
• Drives a workstream or project consisting of one or more infrastructure engineering technologies and works with other platforms to architect and implement changes required to resolve issues and modernize the organization and technology processes
• Strongly considers upstream and downstream data and systems or technical implications and advises on mitigation actions
• 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.
• Provides deep technical support across multiple cloud platforms for thousands of technologists by troubleshooting and resolving complex, integration-level issues above the API layer.
• Builds and improves self-service capabilities (tools, telemetry, guides, FAQs, automation) that help clients and teams resolve issues independently.
• 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.

• 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
• 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.
• Deep knowledge of one specific infrastructure technology and scripting languages
• Deep knowledge of cloud infrastructure and multiple cloud technologies with the ability to operate in and migrate across public and private clouds
• Drives to continue to develop technical and cross-functional knowledge outside of the product.
• 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.
• AWS certification(s).