In this high-impact role, you can step up as a tech leader and innovator by providing your knowledge and mentorship to infrastructure engineers. Lead teams towards excellence and demonstrate your skills as a leader.
As a Senior Manager of Infrastructure Engineering at JPMorganChase within the Consumer and Community Banking, you provide overall direction for team members and work on established and moderately complex issues within your specialization. Exercise independent judgement within defined parameters to determine appropriate actions to bring these issues to a resolution.
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
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.
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