Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
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
Advanced in one or more programming languages including Python
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- In-depth knowledge of the financial services industry and their IT systems
- Practical cloud native experience
Deep, hands-on production experience across the Python + Node.js + React stack at scale, with the ability to set standards for API design, frontend architecture, and cross-tier performance/security.
Track record leading design and delivery of cloud-native services (AWS preferred), including containerization, IaC (Terraform), and CI/CD automation.
Demonstrated ability to mentor associates, run design reviews, and drive technical decisions across a team of engineers.
Preferred qualifications, capabilities, and skills
Frontend performance, accessibility (WCAG), and design-system patterns.
Experience introducing or scaling AI-assisted engineering practices (Copilot-class tooling) within a delivery team — ties back to the AI bullets already in the required section.
Familiarity with the JPMC control environment (SEAL, HLDD, ARB).
Shaping the technical roadmap for a customer-facing or internal developer platform.
