Sr. Director of Software Engineering

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Corporate Sector

Sr. Director of Software Engineering for Audit Tech team, responsible for leading multiple software engineering teams, defining strategy for AI-enabled engineering and SDLC/TLM automation, and overseeing the full software development lifecycle. The role involves driving adoption of AI tools and operating models, managing resources, and ensuring adherence to responsible AI risk and controls.

What you'd actually do

  1. Define strategy, vision, alignment to architecture standards and data strategy , use of AI to advance envisioned transformation and technology selection.
  2. 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.
  3. 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.
  4. Lead and manage multiple software engineering teams, fostering a culture of innovation and continuous improvement
  5. Partner with senior stakeholders, business users and product leadership, tech leadership across Audit & Corporate Technology to build strong partnerships

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
  • Strong background in financial technology and understanding of data-intensive applications
  • Expertise in Java programming and familiarity with Python and Angular
  • Experience with cloud technologies, particularly AWS
  • Proficiency in Oracle database management and optimization
  • Proven track record of successfully leading large-scale software development projects
  • Strong knowledge of Agile methodologies and DevOps practices
  • Demonstrated ability to work effectively with business stakeholders and technical teams
  • Experience in managing budgets and resources for software development projects
  • 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

  • deep working knowledge of public cloud, native-cloud applications, microservices, databases, data lakes
  • Ensure all software development adheres to financial industry regulations and security standards

What the JD emphasized

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

Other signals

  • AI-enabled engineering
  • agentic AI-enabled engineering
  • AI-orchestrated delivery workflows
  • AI-assisted development