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JPMorgan Chase & Co.

Lead Software Engineer - Java & AWS

JPMorgan Chase & Co. · Bengaluru, Karnataka, India

Financial Services · 10,001+ employees

6 h ago Closes in 2d
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 the adoption of AI-assisted engineering practices. They will also lead technical evaluation sessions and foster communities of practice to promote innovation and operational stability.

What they look for

Java J2EE Spring Boot Microservice Architecture AWS Terraform Github Copilot Jenkins Data Science Graph SQL PostgreSQL MySQL DynamoDB Docker Kubernetes

Requirements

Candidates must have 5+ years of experience in system design, application development, and operational stability with proficiency in Java, AWS, and microservices. Strong leadership skills and experience with AI-assisted development tools are required to guide teams and ensure high-quality code delivery.

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 & Community Banking Technology Team, 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
  • 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
  • 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

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience in system design, application development, testing, and operational stability
  • Core Skills - Java/J2EE, Spring Boot, Microservice architecture, AWS, Terraform, Github, Copilot, Jenkins, Data Science, Graph SQL
  • Databases: Proficiency with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., DynamoDB, Redis, Cassandra) and Graph SQL.
  • Containerization: Experience with Docker and container orchestration (ECS, EKS, or Kubernetes).
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
  • 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
  • Demonstrable ability to code in one or more languages
  • Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Demonstrated expertise with monitoring/observability tools (e.g., Splunk, Datadog, Dynatrace, CloudWatch) and proven capability to lead high-performing teams—driving innovation, maintaining strong team health, and owning the end-to-end team performance cycle.

 Preferred qualifications, capabilities, and skills

  • Familiarity with modern front-end technologies
  • AWS Certification (e.g., Solutions Architect – Associate/Professional, Developer – Associate).
  • Exposure to cloud technologies