Lead Software Engineer Java AWS kafa

JPMorganChase; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

JPMorganChase in Bengaluru seeks a Lead Software Engineer to design, build, and deliver secure, scalable software within the Consumer and Community Banking Technology group. The role is a core technical contribution across multiple business functions, with emphasis on robust SDLC practices and production readiness.

The position requires proven expertise in Java, Spring Boot, Spark, AWS, and NoSQL, along with experience leading architectural discussions and implementing AI-assisted development

Qualifications

• Formal training or certification in software engineering.
• 5+ years of applied software engineering experience.
• Experience delivering design, development, testing, and operations.
• Familiarity with AI-assisted development tools and secure coding practices.

Responsibilities

• Executes innovative software solutions and troubleshoots complex design problems.
• Develops secure, high-quality production code and reviews peers' work.
• Drives AI-assisted engineering practices to improve quality and speed.
• Leads evaluation and architecture discussions with stakeholders and vendors.

Skills

Java

Spring Boot

System design

Production code

AI-assisted development

CI/CD

Agile methodologies

Education

Software engineering certification

Tools

AWS

Apache Spark

Kafka

NoSQL

Job description

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 theConsumer and Community Banking 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 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 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 system design, application development, testing, and operational stability
• Advanced in Java, Springbok, nosql , Apache Spark, AWS, Kakfa
• 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
• Proficient in all aspects of the Software Development Life Cycle
• 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
• Practical cloud native experience