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Salary
≈ $171k – $346k per year (Estimated)
Location
In office (Wilmington)
Seniority
Staff · 5+ years exp
Visa
H-1B filings in 12 months: 3,429 · for this role: 1,686 · green card filings: 933

Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Oct 12, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within Consumer & Community Banking in the Data Technology space, you will be part of an agile team building and delivering secure, stable, and scalable technology products. You will drive significant business impact through technical leadership, architecture and design influence, and hands-on delivery across multiple technologies and applications.

Job Responsibilities

  • Provides technical guidance and direction to support the business and its engineering teams, contractors, and vendors.
  • Designs and develops secure, high-quality production code; reviews, debugs, and raises the engineering bar through strong code review practices.
  • Leads system design and implementation for cloud-native services on AWS, including APIs, standalone services, and event-driven components.
  • Drives decisions that influence product design, application functionality, and technical operations and processes.
  • Drives adoption and governance of approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis).
  • Establishes measurable validation standards for AI-assisted workflows (secure coding, peer review, automated testing) and promotes reuse of proven patterns and automation within the SDLC/toolchain.
  • Applies SDLC toolchain expertise (CI/CD, testing, IaC, observability) to improve reliability, delivery throughput, and operational excellence.
  • Serves as a function-wide subject matter expert in one or more areas of focus and contributes to the engineering community as an advocate of firm-wide frameworks, tools, and practices.

Required Qualifications, Capabilities, and Skills

  • Formal training or certification in software engineering concepts and 5+ years of applied experience.
  • Hands-on experience delivering mission-critical production services with strong contributions to system design, application development, testing, capacity planning and operationalization.
  • Proficient in one or more programming languages (Java, Python, or Go) with strong AWS experience.
  • Strong experience with AWS services to host APIs, run applications, enable inter-application messaging, and implement event-driven services.
  • Experience organizing Terraform workspaces and developing Terraform code (infrastructure as code).
  • Experience designing and developing microservices and backend services.
  • Experience designing backend data models, working with databases (relational and/or NoSQL) and developing non-trivial SQL queries
  • Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment, including setting team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows (data sensitivity, secure handling of inputs/outputs, resiliency and security expectations) and experience coaching engineers/leads on compliant usage patterns and controls.
  • Ability to tackle complex design and functionality problems independently with limited oversight.

Preferred Qualifications, Capabilities, and Skills

  • Experience with messaging/eventing systems (e.g., Kafka, SNS/SQS, Kinesis, MQ).
  • Experience with Docker/containerization best practices and CI/CD pipeline tooling.
  • Understanding of security best practices and secure coding principles.
  • Experience with test-driven development (TDD), automated testing frameworks, and modern API design patterns.
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