Lead Software Engineer- Java Fullstack

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

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 Commercial & Investment Bank, 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
• Delivers end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.
• Uses domain modeling techniques to build best-in-class business products, structuring software for clarity, testability, and evolution.
• 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 communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.
• Investigates and resolve issues, ensuring they do not resurface. Updates technologies and patterns to keep systems current.
• Designs and build solutions that avoid single points of failure using scalable architectural patterns. Designs and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.
• 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.
  
  

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Proficiency in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, Typescript, React, Angular).
• Demonstrated ability to independently solve design and functionality challenges with minimal supervision.
• Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.
• Hands-on experience designing and building scalable applications using Oracle databases. Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle.
• Understanding of application resiliency. 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 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
  
  

• Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.
• Strong problem-solving, analytical, and communication skills.
• Ability to drive broader impact by sharing and contributing best practices.
• Experience in the banking domain. AWS certification.