Lead Software Engineer Java Fullstack React AWS at JPMorgan Chase & Co. in Bengaluru, Karnataka, India

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 JPMorgan Chase within the Consumer & Community Banking Digital Channels, you are an integral part of an agile team that designs, builds, and delivers trusted, market‑leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for promoting critical technology solutions across multiple technical domains and business functions, ensuring they align with and advance the firm’s strategic objectives.

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

Requirements

• Formal training or certification in software engineering concepts with 5+ years of applied experience.
• 10+ years of professional software engineering experience building and operating backend services using Java (11/17+) and Spring Boot (Spring MVC/WebFlux, Spring Security).
• Proven experience designing and delivering distributed systems using patterns such as caching, idempotency, retries, rate limiting, and circuit breakers.
• Hands-on AWS experience across multiple services, including ECS/EKS/Lambda, API Gateway/ALB, VPC, and Route 53.
• Experience with data persistence and storage solutions including RDS/Aurora/PostgreSQL, DynamoDB, and S3, plus caching with ElastiCache.
• Experience implementing event-driven and streaming architectures using SQS/SNS/Kinesis/MSK (or Kafka) and workflow orchestration using Step Functions.
• Demonstrated proficiency with CI/CD and Infrastructure as Code using Terraform/CloudFormation/CDK and Git-based pipelines (e.g., Jenkins, GitHub Actions).
• 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
• Advanced understanding of agile delivery practices, including CI/CD, application resiliency, and secure-by-design engineering.
• Strong communication skills and engineering judgment, with the ability to own services end-to-end in a regulated, financial services environment.

Skills

Required

• Java (11/17+)
• SQS/SNS/Kinesis/MSK (or Kafka)
• Step Functions
• Terraform/CloudFormation/CDK
• AI-assisted software development tools
• CI/CD
• Agile delivery practices
• Secure-by-design engineering