JPMorgan Chase & Co.

Lead Software Engineer - Java, AWS

JPMorgan Chase & Co. Bengaluru, Karnataka, India

Financial Services · 10,001+ employees

8 h ago
java Senior (5-10 yrs) Full-time India
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About the role

The Lead Software Engineer will design, develop, and troubleshoot secure software solutions while driving team adoption of AI-assisted engineering practices. They are responsible for providing technical guidance to the team, managing stakeholder relationships, and ensuring compliance with business requirements.

What they look for

Java AWS Microservices Kafka Agile CI/CD System Design Application Development Automation Cloud Native EKS ECS Distributed Compute Database Management AI-assisted Engineering Software Troubleshooting

Requirements

Candidates must have 5+ years of applied experience in software engineering, including hands-on development with Java microservices and AWS cloud infrastructure. Proficiency in agile methodologies, CI/CD, and event-driven architectures like Kafka is required, along with experience in leading teams and utilizing AI-assisted development tools.

Full 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 the Payments 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.
  • Provides guidance to immediate team of software engineers on daily tasks and activities
  • Sets the overall guidance and expectations for team output, practices, and collaboration
  • Anticipates dependencies with other teams to deliver products and applications in line with business requirements
  • Manages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and business requirements

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

  • Proficient in automation and continuous delivery methods
  • Experience of Java Micro-service architecture, hands on development working at code level
  • Working knowledge of AWS products such as EKS, ECS and distributed compute & database
  • Working knowledge of Kafka & messaging platforms for event driven workflow
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • 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
  • In-depth knowledge of the financial services industry and their IT systems
  • Practical cloud native experience

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