Sr Director of Software Engineering

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Consumer & Community Banking

Senior Director of Software Engineering to lead multiple technical areas and departments, driving the adoption and implementation of agentic AI-enabled engineering and SDLC/TLM automation within a financial services context. The role focuses on setting and scaling strategy, establishing governance, and ensuring responsible AI practices.

What you'd actually do

  1. Sets and scales multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation (using enterprise-authorized tools within the work environment) to drive firmwide objectives (speed, scalability, reliability, and cost-to-serve), including portfolio-level standards for AI-orchestrated delivery workflows, release governance, automated test modernization, resilience engineering, and incident response acceleration; establishes guardrails for validation, security, resiliency, traceability, and reuse.
  2. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive cross-domain reuse and measurable capacity unlock outcomes across departments.
  3. Provides leadership and high-level direction to teams while frequently overseeing employee populations across multiple platforms, divisions, and lines of business
  4. Acts as the primary interface with senior leaders, stakeholders, and executives, driving consensus across competing objectives
  5. Manages multiple stakeholders, complex projects, and large cross-product collaborations

Skills

Required

  • 10+ years applied software engineering experience
  • 5+ years of experience leading technologists
  • Experience developing or leading large or cross-functional teams of technologists
  • Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale
  • Experience leading multi-organization adoption of agentic AI-enabled engineering operating models
  • Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale
  • Experience leading complex projects supporting system design, testing, and operational stability
  • Experience with hiring, developing, and recognizing talent
  • Extensive practical cloud native experience

What the JD emphasized

  • agentic AI-enabled engineering
  • SDLC/TLM automation
  • AI-orchestrated delivery workflows
  • Experience leading multi-organization adoption of agentic AI-enabled engineering operating models (using enterprise-authorized tools within the work environment), including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs across teams.
  • Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies.

Other signals

  • agentic AI-enabled engineering
  • SDLC/TLM automation
  • AI-orchestrated delivery workflows
  • responsible AI risk, controls, and resiliency/security