Senior Director of Software Engineering - Executive Director

JPMorgan Chase JPMorgan Chase · Banking · LONDON, United Kingdom · Corporate Sector

Senior Director of Software Engineering to lead strategy and development for agentic AI-enabled engineering and SDLC/TLM automation within Cloud Foundation Services at JPMorgan Chase. This role involves setting and scaling multi-department strategy, establishing guardrails for AI-orchestrated workflows, and driving adoption of AI-assisted development tools to improve speed, scalability, reliability, and cost-to-serve. Requires deep understanding of responsible AI risk, controls, and resiliency at scale, with experience leading multi-organization adoption of agentic AI operating models.

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. Advises and leads on the strategy and development of multiple products, applications, and technologies across a portfolio
  4. Creates novel code solutions and drives the development of new production code capabilities across teams and functions
  5. Translates highly complex technical issues, trends, and approaches to leadership to drive the firm’s innovation and enable leaders to make strategic, well-informed decisions about technology advancements

Skills

Required

  • Proven software engineering experience
  • Practical experience delivering system design, application development, testing, and operational stability
  • Expert in one or more programming language(s): Java, Go, Python, Rust, etc.
  • Demonstrated prior experience with influencing across functions and teams and delivering value at scale
  • Experience applying expertise and new methods to determine solutions for complex technology problems across various technical disciplines
  • Extensive practical cloud native experience
  • Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field
  • 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

Nice to have

  • Strong experience with cloud-native architecture, event-driven architecture, test-driven development
  • Domain-level expertise in building continuous compliance systems at scale in financial services
  • Expert-level understanding and experience with regulatory and industry standards relating to technology controls in financial services

What the JD emphasized

  • agentic AI-enabled engineering
  • SDLC/TLM automation
  • AI-orchestrated delivery workflows
  • agentic AI-enabled engineering operating models
  • responsible AI risk, controls

Other signals

  • AI-enabled engineering
  • SDLC/TLM automation
  • AI-orchestrated delivery workflows
  • agentic AI-enabled engineering operating models
  • responsible AI risk, controls