Sr Director of Software Engineering Equity Derivatives Technology

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Commercial & Investment Bank

Senior Director of Software Engineering for Equity Derivatives Technology at JPMorgan Chase, focusing on leading multiple technical areas and managing departments. The role involves driving the adoption and implementation of agentic AI-enabled engineering and SDLC/TLM automation to improve speed, scalability, reliability, and cost-to-serve, including setting standards for AI-orchestrated delivery workflows, automated testing, resilience engineering, and incident response. Requires experience in leading large, cross-functional teams, influencing complex organizations, and deep understanding of responsible AI risk and controls.

What you'd actually do

  1. Leads multiple technology and process implementations across departments to achieve firmwide technology objectives
  2. Directly manages multiple areas with strategic transactional focus
  3. 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.
  4. 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.
  5. Provides leadership and high-level direction to teams while frequently overseeing employee populations across multiple platforms, divisions, and lines of business

Skills

Required

  • Formal training or certification on software engineering concepts
  • 10+ years applied software engineering experience
  • 5+ years of experience leading technologists to manage, anticipate and solve complex technical items
  • 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
  • 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
  • Demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies
  • Experience leading complex projects supporting system design, testing, and operational stability
  • Experience with hiring, developing, and recognizing talent
  • Extensive practical cloud native experience

Nice to have

  • Understanding of Equity Derivative products
  • Strong technical skill in object-based databases
  • Experience development in Java, python or C++

What the JD emphasized

  • agentic AI-enabled engineering
  • SDLC/TLM automation
  • AI-orchestrated delivery workflows
  • automated test modernization
  • incident response acceleration
  • responsible AI risk
  • portfolio governance
  • human-in-the-loop decisioning
  • quality gates
  • measurement frameworks
  • secure handling of sensitive inputs/outputs

Other signals

  • agentic AI-enabled engineering
  • SDLC/TLM automation
  • AI-orchestrated delivery workflows
  • automated test modernization
  • incident response acceleration
  • responsible AI risk
  • portfolio governance