JPMorgan Chase & Co.

Lead Software Engineer - Java, AWS

JPMorgan Chase & Co. · Hyderabad, Telangana, India

Financial Services · 10,001+ employees

6 h ago Closes in 1d
Senior (5-10 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 of architectural designs.

What they look for

Java AWS Spring Boot Microservices SQL Oracle PostgreSQL Terraform CloudFormation CI/CD AI-assisted Engineering System Design

Requirements

Requires 5+ years of experience in Java and AWS, with demonstrated expertise in microservices and RDBMS. Must have experience in coaching, mentoring, and implementing CI/CD and cloud infrastructure provisioning 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 Consumer and Community Banking, 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
  • 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 Java concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience..
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Proficiency with programming languages like Java is a must, SQL and experience in Spring boot, Micro services, AWS
  • Hands-on experience in RDBMS; Oracle or PostgresSQL
  • Proficiency in automation and continuous delivery methods
  • Hands-on experience in AWS EC2, AWS Lambda, AWS KMS, AWS ECS, AWS EKS, AWS S3, EMR, Athena, SQS, EventBridge, PostgresSQL
  • Hands-on experience with Cloud Infrastructure Provisioning Tools like Terraform & Cloud Formation etc
  • 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.)
  • 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