Salary
≈ $172k – $349k per year (Estimated)
Location
In office (New York)
Seniority
Staff
Overview
Company
Impact
Profile match
JPMorgan Chase & Co. is a leading global financial services firm and the largest banking institution in the United States by assets. Headquartered in New York City, the company offers a comprehensive range of financial solutions, including investment banking, asset management, treasury services, and commercial banking. Through its widely recognized consumer division, Chase, it delivers retail banking, credit card, and mortgage services to tens of millions of households across the globe.
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 JPMorganChase within the Data Management/Data Tech, 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
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
- Lead with an AI-driven approach in daily tasks
- Spearhead the design and development of real-time, mission-critical using Java
- Tackle large-scale engineering challenges with technologies like Kafka
- Innovate, troubleshoot, and optimize for performance and stability
- Inspire and foster a culture of creativity, inclusion, and technical excellence
- 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
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
- 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
Required qualifications, capabilities, and skills
- 5+ years of relevant software engineering experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s)
- Proficiency in automation and continuous delivery methods
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- 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
- 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
Preferred Qualifications, Capabilities, and Skills:
- Expertise in GenAI usage, transforming Software Engineering with an AI-first approach
- Experience with both Java and Python development
- Proficiency in Java/Spring, data structures, AWS, Terraform and performance tuning
- Solid experience with Kafka
- Proficiency in testing and debugging low latency applications
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