Senior Lead Infrastructure Engineer - Capacity Management

Job responsibilities

• Applies deep technical expertise and problem-solving methodologies focused on analyzing complex data and systems, anticipating issues, and finding ways to mitigate risk
• Works with other platforms to architect and implement changes required to resolve issues and modernize the organization and its technology processes
• Be responsible for infrastructure engineering in accordance with business requirements
• Drives results and implements multiple complex programs
• Drives thought leadership within the product line
• Executes work according to compliance standards, risk and security, and business objectives
• Considers upstream/downstream system or technical implications and advises on mitigation actions
• Advises junior engineers and technologists
• Uses enterprise-authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements.
• Leads reuse-first adoption of AI-assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• 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

• Experience with creating and leveraging dashboards (Grafana, Dynatrace, ELK,.) for visualization of data.

• Experience on business intelligence (BI) tools like Microsoft Power BI, Qlik, Tableau etc. that allow users to explore and analyze data from multiple sources. 

• Experience managing the lifecycle of cross-functional projects, implementing automated equipment and/or integrated systems. Ability to navigate effectively, building partnerships with exceptional communication skills.

• Strong knowledge of one or more scripting languages (e.g., Go, JavaScript, Python, etc.)

• Deep technical knowledge across multiple domains
• 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.

Preferred qualifications, capabilities, and skills

• Exposure to managing budgets