Senior Manager of Software Engineering

JPMorganChase•Jersey City, NJ

About The Position

As a Senior Manager of Software Engineering at JPMorganChase, you provide technical coaching and advisory support to multiple technical teams and anticipate the needs and potential dependencies of other functions within the firm. Your expertise informs budget and technical considerations to advance operational efficiencies and functionality. You lead teams of entry-level to mid-level software engineers and are accountable for decisions affecting team resources, budgets, tactical operations, and the execution and implementation of processes and procedures. You establish and scale operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across teams, setting measurable expectations and ensuring validation, security, resiliency, and reuse of proven patterns. You use software development lifecycle toolchain capabilities to improve efficiency and support capacity initiatives, prioritizing existing firm technology assets. You also collaborate across teams and stakeholders, address delivery issues, and advise leadership on approaches and technical considerations.

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience.
At least 2 years of experience leading technologists to manage and solve complex technical items within the relevant domain.
Experience leading teams of technologists.
Ability to guide and coach teams on approaches for achieving goals aligned with strategic initiatives.
Required full-stack experience with Java, Node.js, Postgres, REST, Kubernetes (K8), CI/CD, and AWS cloud.
Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance and ways of working such as human-in-the-loop validation and quality gates, measuring outcomes, and ensuring secure handling of sensitive inputs and outputs.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency and security implications, and control expectations.
Experience hiring, developing, and recognizing talent.
In-depth knowledge of the services industry and its IT systems.
Practical cloud-native experience.

Nice To Haves

Experience working at code level.
Experience with Temporal.
Payments domain experience.

Responsibilities

Provide overall direction, oversight, and coaching for entry-level to mid-level software engineers working on basic to moderately complex tasks.
Make decisions influencing teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures.
Set and scale operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams.
Establish measurable expectations, such as throughput, defect reduction, and reliability, and ensure consistent validation, security, resiliency, and reuse of proven patterns.
Use software development lifecycle toolchain capabilities, including enterprise-authorized AI-assisted development and automation, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.
Ensure successful collaboration across teams and stakeholders.
Identify and mitigate issues to execute a book of work, escalating issues as necessary.
Provide input to leadership regarding budget, approach, and technical considerations to improve team operational efficiencies and functionality.
Lead multi-team adoption of AI-assisted development and delivery tools, including defining governance and ways of working, measuring outcomes, and ensuring secure handling of sensitive inputs and outputs.
Coach managers and leads and influence leaders on safe scaling patterns for responsible AI use in engineering workflows.