JPMorgan Chase
From JPMorgan Chase's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
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 Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
Drive architectural decisions for distributed systems including event-driven pipelines, CQRS patterns, and real-time data streaming
Develops secure high-quality production code, and reviews and debugs code written by others
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
Adds to team culture of diversity, opportunity, inclusion, and respect
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
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.
Formal degree or certification on software engineering concepts and 5+ years applied experience developing UI’s with hands-on applied experience developing in React
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security, and Software Development Lifecycle
Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
In-depth knowledge of the financial services industry and their IT systems
Practical cloud native experience
Experience in developing, debugging and automated testing (e.g. react testing library / cypress) within a commercial setting
Experience collaborating with backend technology teams in designing scalable and reusable RESTful APIs
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
Exposure to frontend libraries such as ag-grid, highcharts, redux as well as Typescript
Exposure to performance tuning complex UI’s would be advantageous.
Working within Investment Bank / Finance Technology
Team management experience
Experience in DevOps model and Kubernetes, cloud auto scalable infrastructure
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