As a Principal Software Engineer (Executive Director) at JPMorganChase within Finance Technology, you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various technologies to support firm's portfolios.
You will spend most of your time hands-on, designing and building the APIs, data pipelines, and integrations that operates on large volume data sets. The remainder goes into setting technical direction , design reviews and defining how teams build & utilizes the solutions.
Job responsibilities
- Creates complex and scalable coding frameworks using appropriate software design frameworks
- Defines and leads multiple technology and process implementations across groups to achieve firmwide technology objectives, working in a matrix model
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- 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, releases 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 and 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
- Influences leaders and senior stakeholders across business, product, and technology teams
- Engineers the platform's query and data access layer over firmwide code intelligence infrastructure, owning query latency, data freshness, resiliency, and cost characteristics as consumption grows across the firm's codebase
- Defines how SDLC controls, compliance checks, and engineering workflows execute against real code structure rather than manual review, and drives adoption by delivering the reference integrations, consumption patterns, and standards other teams build against
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and advanced applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Expert in one or more programming language(s), preferably Java
- 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, grounded in a strong understanding of responsible AI use, control expectations, and risk-based governance in engineering workflows
- 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
- Practical cloud native experience
- Demonstrated experience designing and operating platform APIs and data services consumed by other engineering teams, including contract design, versioning, and backward compatibility as the consumer base grows
- Hands-on experience building high-volume, data-intensive systems where query latency, data freshness, and index or storage design determine whether the product is usable, including the associated capacity, cost, and resiliency trade-offs
- Experience delivering an internal platform as a product, establishing the consumption patterns, reference implementations, and documentation that drive measurable adoption across multiple teams, and evolving that platform without breaking existing consumers
Preferred qualifications, capabilities, and skills
- Experience working with structured representations of source code, such as abstract syntax trees, symbol or dependency graphs, or large-scale code search indexes, and exposing them through queryable interfaces
- Experience automating SDLC controls, audit evidence collection, or change management and regulatory checks in a controlled or regulated engineering environment
- Experience building developer-facing tooling or platforms adopted across a large engineering organization, including supplying trustworthy code context to AI-assisted development tools