• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• 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
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

• 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
• Deep knowledge multiple infrastructure technologies and scripting languages (e.g., Python, JavaScript, yaml, Json, Bash, etc.)
• Deep knowledge of cloud infrastructure and multiple cloud technologies with the ability to operate in and migrate across public and private clouds
• Knowledge of on-premises and remote Data Center technologies and operations
• Strong experience in several OS and Hypervisor platforms (Hyper-V, ESXi, KVM, VMWARE, OpenShift)
• Experience in infrastructure automation, optimization and observability
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
• Experience in deploying and using telemetry tools to improve visibility in service offerings
• Solid understanding of public cloud technologies, for AWS / Azure on Kubernetes, Terraform, experience in CI/CD and tools like Ansible, Terraform, Puppet for automating configuration management and deployment processes

High Risk Roles (HRR) are sensitive roles within the technology organization that require high assurance of the integrity of staff by virtue of 1) sensitive cybersecurity and technology functions they perform within systems or 2) information they receive regarding sensitive cybersecurity or technology matters. Users in these roles are subject to enhanced pre-hire screening which includes both criminal and credit background checks (as allowed by law). The enhanced screening will need to be successfully completed prior to commencing employment or assignment.