JPMorgan Chase & Co.

Lead Software Engineer - Java

JPMorgan Chase & Co. · Bengaluru, Karnataka, India

Financial Services · 10,001+ employees

7 h ago Closes in 4d
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 a culture of inclusion and operational stability within the agile team.

What they look for

Java Spring Python Git Jira ServiceNow System Design Application Development CI/CD Agile Methodologies SQL NoSQL RESTful APIs Automated Testing Cloud Technologies DevOps

Requirements

Candidates must have 5+ years of applied software engineering experience with proficiency in Java, Spring, and Python. A strong understanding of the Software Development Life Cycle, agile methodologies, and experience with AI-assisted development tools is required.

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 JPMorgan Chase within the Commercial & Investment Bank Securities Services 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
  • 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 5+ years applied experience
  • Proficiency in Java, Spring, and Python.
  • Experience with version control systems (e.g., Git) and workflow management systems such as JIRA or ServiceNow.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced in one or more programming language(s)
  • Proficiency in automation and continuous delivery methods. Proficient 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.)
  • 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

  • Exposure to cloud technologies (AWS, Azure, GCP) or DevOps practices.
  • Knowledge of databases (SQL, NoSQL) and RESTful APIs.
  • Experience with automated testing frameworks.
  • Exposure to coding assistants such as GitHub Copilot.