Job responsibilities

• Serves in a leadership role for multiple technical teams and collaborates with others within the function, providing tasks, guidance and expectations as necessary

• Drives reuse-first adoption of enterprise-authorized AI capabilities within the work environment across teams to improve delivery speed and decision quality (e.g., accelerating issue analysis and documentation), with human-in-the-loop validation and appropriate handling of sensitive data.

• Anticipates the needs and potential dependencies of the broader team and identifies and takes action to mitigate and escalate issues to appropriate leadership

• Manages stakeholders and ensures teams deliver aligned projects in line with compliance standards, risk and security, service level agreements, and business requirements

• Applies relevant technical expertise, leadership and business knowledge to projects of moderate to large scope

• Contributes to decisions that influence staffing, budget, and relevant profit and loss

• Establishes standards for AI-assisted workflows used in delivery and operational routines, ensuring traceability and auditability and alignment to resiliency, security, and risk expectations.

Required qualifications, capabilities, and skills

• Formal training or certification on infrastructure engineering concepts and 5+ years applied experience 
• 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
• Hands-on experience with AWS/Azure Cloud platforms and Python or other scripting tools
• Hands-on with Git, CI/CD pipelines, and DevOps deployment practices. Experience with reporting and dashboarding using at least one data visualization platform (e.g., Tableau). Experience with CMDB-type inventory management and reporting tools such as ServiceNow and with any observability platforms such as Splunk, Grafana, Dynatrace. 
• Use Agile practices and backlog & prioritization tools such as Jira to plan, build and deliver the work. Turning Manual into automated workflows on a continuous basis
• Knowledge of how infrastructure assets (Cloud, on-prem, private Cloud, SaaS)are registered, stored, and tracked through end-to-end life cycle. Ability to shift from reactive to proactive methodologies to remediate and mitigate security risks. Strong background in Tech Risk & Controls oversight, monitoring, and reporting, with proven ability to execute controls framework activities in partnership with technology and risk stakeholders
• Understanding of ITAM lifecycle governance and how asset inventory and classification impact control effectiveness and findings

• Experience leading teams in the safe use of enterprise-authorized AI capabilities within the work environment for infrastructure engineering workflows, including validation habits and awareness of data sensitivity.

• Ability to review and validate AI-assisted recommendations before adoption, escalate uncertainty appropriately, and ensure outcomes align to resiliency, security, and auditability expectations.

• Partner with Security, risk, control partners, and the technology teams as the primary ITAM subject matter expert. Experience managing, coaching, and mentoring teams, and fostering a high-performance culture within the team