at J.P. Morgan
Bulge Bracket Investment BanksPosted 10 days ago
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**Lead Software Engineer** at JPMorganChase drives trusted, scalable tech solutions across Asset & Wealth Management. Leads team in designing, developing, and maintaining enterprise-level applications using **Java**, **Spring Boot**, and **Kafka**. Manages end-to-end delivery, inclusive of **AWS** cloud native architecture designs and deployments. Enhances code quality via enterprise-authorized AI-assisted tools, driving automation and secure coding practices. Critical role requires 5+ years' experience, including complex distributed systems delivery. **Agile** methodologies proficiency essential.
- Compensation
- Not specified
- City
- Bengaluru
- Country
- India
Currency: Not specified
Full Job Description
Location: Bengaluru, Karnataka, India
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 Asset and Wealth Management, 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 firms business objectives.
Job responsibilities
As a Lead Software Engineer at JPMorganChase within Asset and Wealth Management, 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 firms 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 breakdown technical problems
- Develops secure and high-quality production code, and reviews and debugs code written by others
- 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.
- 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 5+ years applied experience
- Hands-on practical experience delivering complex distributed system design, application development, testing, and operational stability
- Advanced in one or more programming language(s) - Java
- Practical cloud native experience - designing, building and deploying applications on Amazon Web Services (AWS)
- Advanced knowledge of Spring Boot and Kafka
- Experience in leading project execution and owning end-to-end delivery
- 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
- 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
Preferred qualifications, capabilities, and skills
- Basic/Intermediate knowledge of Python
- Experience with either Snowflake or DataBricks
