Lead Software Engineer-full Stack

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

Lead Software Engineer focused on integrating AI assistants into the software development lifecycle at JPMorgan Chase. The role involves designing and implementing features, ensuring operational excellence, championing secure designs, and establishing governance for AI use, including prompt hygiene, PII protection, and outcome measurement. The engineer will also write production code, integrate with databases, and lead design reviews.

What you'd actually do

  1. Integrates firm approved, privacy safe AI assistants into day to day development to accelerate test generation, documentation, refactoring, and static analysis triage—always with human in the loop review and CI quality gates.
  2. Establishes guardrails and governance for AI use: prompt hygiene, secrets/PII protection, logging/provenance for generated code, and objective acceptance criteria: lint clean, coverage thresholds, Static App Security Tests/Dynamic App Security Tests, performance checks.
  3. Defines and track measurable outcomes from AI assisted workflows: developer throughput, review cycle time, defect density without compromising security or reliability.
  4. Leads design and implementation of complex features and services across upstream/downstream services; define API contracts, versioning, and backward compatibility.
  5. Owns production readiness and operational excellence: define SLOs/SLIs, drive observability (logs, metrics, traces), manage incidents, and reduce MTTR through durable fixes and runbooks.

Skills

Required

  • Java and Spring Boot development
  • SQL
  • AWS and cloud‑native services
  • Javascript, HTML 5, CSS3
  • system design
  • RESTful JSON API design
  • micro services
  • application development
  • testing strategy
  • operational stability
  • Software Development Life Cycle (SDLC)
  • CI/CD pipelines
  • automated testing
  • security and resiliency
  • AI‑led development: operational experience integrating approved AI assistants into development workflows with governance, human review, and measurable outcomes.

Nice to have

  • .NET/C#
  • Typescript and React
  • Travel or hospitality domain experience
  • Experience introducing evaluation frameworks for AI-assisted development or AI features
  • frontend performance and accessibility practices

What the JD emphasized

  • AI assistants into day to day development
  • human in the loop review
  • CI quality gates
  • guardrails and governance for AI use
  • measurable outcomes from AI assisted workflows
  • AI-led development: operational experience integrating approved AI assistants into development workflows with governance, human review, and measurable outcomes.

Other signals

  • integrating AI assistants into development workflows
  • establishing guardrails and governance for AI use
  • defining and track measurable outcomes from AI assisted workflows