Lead Software Engineer - Java Full Stack

JPMorganChase · Bengaluru · 5+ yrs experience · Posted 2026-07-06

Apply on the company site · Get a referral for this role

JPMorganChase salary & ratings · JPMorganChase interview process · More live openings

About the role

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 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 firm’s business objectives.
Responsibilities:
- EServe as a hands-on technical contributor delivering critical solutions across business functions aligned to firm objectives.
- Develop secure, high-quality production code; review, debug, and provide feedback on code written by others.
- Identify recurring issues and implement automation and/or durable remediation to improve operational stability and resiliency.
- Lead evaluation sessions with technology partners to drive outcome-oriented review and validation of architectural designs and trade-offs.
- Lead and contribute to communities of practice across Software Engineering to promote adoption of leading-edge technologies and engineering standards.
- 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.
Qualifications:
- Formal training or certification in software engineering concepts with
- 5+ years
- of applied engineering experience.
- Strong knowledge of modern architectures, including
- microservices
- REST APIs
- NoSQL data stores
- event-driven
- patterns.
- Experience building
- cloud-native
- applications and services. Working knowledge of
- (or a comparable cloud platform).
- Demonstrated experience delivering at least
- large, complex applications end-to-end (from initial build through production delivery), ideally within a large financial institution or a world-class product engineering organization.
- Working knowledge of
- DevOps toolchains
- , software monitoring/observability, and a
- test-driven
- approach within agile delivery.
- Strong collaboration skills, with the ability to execute multiple parallel workstreams with engineers, analysts, and cross-functional partners.
- Advanced understanding of
- application resiliency
- security
- principles and practices.
- Strong technical documentation skills (e.g., API documentation using
- OpenAPI/Swagger
- Familiarity with AI concepts and developer productivity tools (e.g., Microsoft Copilot or similar).
- 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
- Experience designing and building
- high-availability
- system architectures.
- Experience driving engineering process improvements and change adoption (including associated culture and ways-of-working changes).

Qualifications

- Formal training or certification in software engineering concepts with 5+ years of applied engineering experience.
- Strong knowledge of modern architectures, including microservices REST APIs
- NoSQL data stores event-driven patterns.
- Experience building cloud-native applications and services.
- Working knowledge of (or a comparable cloud platform).
- Demonstrated experience delivering at least large, complex applications end-to-end (from initial build through production delivery), ideally within a large financial institution or a world-class product engineering organization.
- Working knowledge of DevOps toolchains software monitoring/observability, and a test-driven approach within agile delivery.
- Strong collaboration skills, with the ability to execute multiple parallel workstreams with engineers, analysts, and cross-functional partners.
- Advanced understanding of application resiliency security principles and practices.
- Strong technical documentation skills (e.g., API documentation using OpenAPI/Swagger Familiarity with AI concepts and developer productivity tools (e.g., Microsoft Copilot or similar).
- 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
- Experience designing and building high-availability system architectures.
- Experience driving engineering process improvements and change adoption (including associated culture and ways-of-working changes).

Responsibilities

- EServe as a hands-on technical contributor delivering critical solutions across business functions aligned to firm objectives.
- Develop secure, high-quality production code; review, debug, and provide feedback on code written by others.
- Identify recurring issues and implement automation and/or durable remediation to improve operational stability and resiliency.
- Lead evaluation sessions with technology partners to drive outcome-oriented review and validation of architectural designs and trade-offs.
- Lead and contribute to communities of practice across Software Engineering to promote adoption of leading-edge technologies and engineering standards.
- 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.

More openings at JPMorganChase