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**Lead Software Engineer - Java Full Stack** - Bengaluru, India Drive critical tech solutions across multiple business functions, building and enhancing secure, stable, and scalable products. Lead an agile team, delivering high-quality code spanning microservices, REST APIs, NoSQL data stores, and event-driven patterns. Requires **5+ years** of engineering experience, strong cloud knowledge (focusing on **AWS**), and proficiency in **Java full stack**, **CI/CD**, and **DevOps toolchains**. Proven experience leading large, complex application builds in financial institutions. Foster AI adoption and promote leading-edge tech standards.

Compensation: Not specified
City: Bengaluru
Country: India

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 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 firms business objectives.

Job 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.

Required qualifications, capabilities, and skills

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, and event-driven patterns.

Experience building cloud-native applications and services. Working knowledge of AWS (or a comparable cloud platform).

Demonstrated experience delivering at least two 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 CI/CD, 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 and 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

Preferred qualifications, capabilities, and skills

Experience designing and building high-availability system architectures.

Experience driving engineering process improvements and change adoption (including associated culture and ways-of-working changes).

Carry out critical tech solutions across multiple technical areas as an integral part of an agile team

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.

Job 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.

Required qualifications, capabilities, and skills

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, and event-driven patterns.

Experience building cloud-native applications and services. Working knowledge of AWS (or a comparable cloud platform).

Working knowledge of CI/CD, 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 and 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).

Preferred qualifications, capabilities, and skills

Experience designing and building high-availability system architectures.

Experience driving engineering process improvements and change adoption (including associated culture and ways-of-working changes).

Carry out critical tech solutions across multiple technical areas as an integral part of an agile team

Lead Software Engineer - Java Full Stack

Full Job Description

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