Director of Software Engineering

JPMorgan Chase JPMorgan Chase · Banking · Wilmington, DE +1 · Consumer & Community Banking

Director of Software Engineering for the Card Line of Business, focusing on leading technology and process implementations. The role involves setting direction and governance for agentic AI-enabled engineering and SDLC/TLM automation, driving improvements in speed, quality, and operational outcomes. Requires experience leading teams, adopting AI-enabled practices, and understanding responsible AI use within engineering workflows.

What you'd actually do

  1. Leads technology and process implementations to achieve functional technology objectives
  2. Makes decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
  3. Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations
  4. Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse across teams.
  5. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation and support capacity unlock initiatives at scale.

Skills

Required

  • Formal training or certification on software engineering concepts and 10+ years applied experience
  • 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
  • Experience developing or leading cross-functional teams of technologists
  • Experience with hiring, developing, and recognizing talent
  • Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
  • Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse.
  • Practical cloud native experience
  • Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field

Nice to have

  • Experience working at code level
  • Practical migration experience from Mainframe to Cloud
  • Building an AI based Regression suite for an application
  • Understanding of the Credit card domain is a plus.

What the JD emphasized

  • agentic AI-enabled engineering
  • responsible AI use
  • guardrails for validation, security, resiliency, traceability, and reuse

Other signals

  • AI-orchestrated delivery workflows
  • agentic AI-enabled engineering
  • responsible AI use
  • guardrails for validation, security, resiliency, traceability, and reuse