As a Principal Software Engineer at JPMorganChase within Consumer & Community Banking, you provide expertise and engineering excellence building and delivering trusted market-leading technology products in a secure, stable, and scalable way.
Job responsibilities
- Creates complex and scalable coding frameworks using appropriate software design frameworks
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.
- 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 at scale.
- Advises cross-functional teams on technological matters within domain of expertise
- Serves as the function’s go-to subject matter expert
- Contributes to the development of technical methods in specialized fields in line with the latest product development methodologies
- Creates durable, reusable software frameworks that are leveraged across teams and functions
- Influences leaders and senior stakeholders across business, product, and technology teams
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 7+ years applied experience
- Extensive experience in GCP or AWS
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Expert in one or more programming language(s) (python, java, go)
- Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
- Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.
- Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplines
- Ability to present and effectively communicate with Senior Leaders and Executives