Director of Software Engineering -payments Investigations

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Commercial & Investment Bank

Director of Software Engineering leading a Payments Investigations team, responsible for driving impact across teams and projects. The role involves setting direction for agentic AI-enabled engineering and SDLC/TLM automation, delivering low-latency solutions, and ensuring responsible AI use with guardrails. Requires extensive experience in full-stack cloud-native distributed systems and leading adoption of AI practices.

What you'd actually do

  1. Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse across teams.
  2. Delivers and owns end-to-end, cutting-edge low latency solutions leveraging the latest technologies and best industry practices
  3. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation and support capacity unlock initiatives at scale.s
  4. Partners with product and business groups to drive participation, plans, timelines, dependencies, and solutions to ensure successful delivery and desired outcomes
  5. Engages with business stakeholders to break down complex and ambiguous problems into technical specifications for engineering teams to implement under your guidance

Skills

Required

  • Formal training or certification on software engineering concepts and 13+ years applied experience, including 5+ years leading technologists to manage, anticipate, and solve complex technical items within your domain of expertise
  • Extensive hands-on experience designing and building full stack cloud native distributed systems with high availability, fault-tolerance, and scalability using Java, Spring, Python, or Camunda
  • Experience handling large volumes of data with databases such as PostgreSQL
  • Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
  • Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse.
  • Understanding and experience with cloud technologies, software engineering/product engineering methods, and technology best practices
  • Demonstrated 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
  • Ability to understand and convey programming models, technologies, systems, and APIs relevant for stakeholders

Nice to have

  • Experience working in payments or investigations domain
  • Experience working at code level
  • Experience developing or leading cross-functional teams of technologists
  • Experience with hiring, developing, and recognizing talent
  • Experience leading a product as a Product Owner or Product Manager
  • Experience working with product teams to ensure understanding and alignment of requirements and technical solutions

What the JD emphasized

  • agentic AI-enabled engineering practices
  • responsible AI use
  • low latency solutions

Other signals

  • AI-enabled engineering
  • agentic AI
  • low latency solutions
  • SDLC/TLM automation
  • responsible AI use