at J.P. Morgan
Bulge Bracket Investment BanksPosted 14 days ago
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**Lead Software Engineer - Java Full Stack | Bengaluru, Karnataka, India** Drive & deliver secure, high-quality Java/Springboot full-stack solutions. Lead team adoption of AI-assisted engineering practices. Collaborate cross-functionally to troubleshoot & automate remediation. Evaluate external vendors & drive architectural design assessments. Proficient in microservices, cloud platforms, flexible databases, & CI/CD. 5+ years of software engineering experience required.
- 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 JPMorgan Chase within the Commercial & Investment Bank, Securities Services 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. 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 JPMorgan Chase within the Commercial & Investment Bank, Securities Services 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. 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.
- Proficiency in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, Typescript, React).
- Demonstrated ability to independently solve design and functionality challenges with minimal supervision.
- Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON. Hands-on experience designing and building scalable applications using SQL and NoSQL databases.
- Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle. Understanding of application resiliency
- Proficiency in automation and continuous delivery methods.
- 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.
- Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
