JPMorgan Chase & Co.

Lead Software Engineer : Java / Backend

JPMorgan Chase & Co. · Bengaluru, Karnataka, India

Financial Services · 10,001+ employees

9 h ago
Principal (10+ yrs) Full-time India
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About the role

Lead the design, development, and troubleshooting of secure, scalable software solutions within an agile team. Drive the adoption of AI-assisted engineering practices and lead technical evaluations with external vendors and internal teams.

What they look for

Java REST API Kafka Spring Boot System Design CI/CD Cloud Native AI-assisted Engineering AWS Agile Methodologies Application Resiliency Security Multi-region Deployments Performance Optimization Observability Tools Blue-Green/Canary Deployments

Requirements

Requires 10+ years of software engineering experience with proficiency in Java, Spring Boot, Kafka, and REST APIs. Candidates must have a strong understanding of cloud-native architecture, CI/CD, and the responsible use of AI tools in development.

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 Markets Experience 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 break down technical problems
  • Develops secure high-quality production code, and reviews and debugs code written by others
  • 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
  • Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
  • Adds to team culture of diversity, opportunity, inclusion, and respect
  • 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 on software engineering concepts and 10+ years applied experience
  • Hands-on experience with Java, REST API, Kafka, Spring Boot
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced understanding of multi-region deployments.
  • Proficiency in automation and continuous delivery methods and in all aspects of the Software Development Life Cycle
  • 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.)
  • In-depth knowledge of the financial services industry and their IT systems. Practical cloud native experience
  • 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

  • AWS experience
  • Experience working with Blue-Green/Canary deployments
  • Experience working with observability tools
  • Experience with performance optimization and trouble shooting