Sr Director of Software Engineering

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Consumer & Community Banking

Senior Director of Software Engineering to lead multiple technical areas and departments, focusing on setting strategic direction and driving the adoption of agentic AI-enabled engineering and SDLC/TLM automation within a financial services context. The role involves collaborating across technical domains, engaging with business stakeholders, and establishing governance, measurement frameworks, and guardrails for AI-driven workflows.

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. Engage with business stakeholders to break down complex and ambiguous problems into technical specifications that an engineering team can implement under your guidance.
  3. Set strategic direction for all aspects of engineering and architecture across your area product.
  4. Carries governance accountability for technology decisions, regulatory compliance, and control obligations
  5. Champion engineering practices; Improve the effectiveness of the Engineering teams through coaching, mentoring and resolution of impediments

Skills

Required

  • Experience working in the Payments domain
  • Extensive hands-on experience in designing and building full stack cloud native distributed systems with high degree of availability, fault-tolerance & scalability using Java Spring.
  • Experience in handling large volume of data with Databases like PostgreSQL, Oracle is critical for the role.
  • 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.
  • Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale
  • Experience managing competing requirements to align product prioritization with technical capacity and feasibility, balancing solution priorities between long-term technical roadmap and short-term execution needs

Nice to have

  • Experience working in a highly regulated environment (e.g. Banking & Finance, Healthcare etc.)

What the JD emphasized

  • agentic AI-enabled engineering
  • responsible AI risk, controls, and resiliency/security expectations at scale
  • governance accountability for technology decisions, regulatory compliance, and control obligations

Other signals

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