Lead Software Engineer - Shared Services
As a Lead Software Engineer - Common Services at JPMorgan Chase within the Risk Technology team, you will be a key player in an agile team, tasked with designing and delivering secure, stable, and scalable market-leading technology products. Your role involves implementing critical technology solutions across various technical areas within different business functions to support the firm's business objectives. Our primary front-end technologies include Typescript, and React, which interface with a Spring Boot back-end and are deployed to Kubernetes-based platforms on both private and public clouds. A significant part of your role will be to ensure that our deployments, conducted via a build server, are efficient and well-controlled.
We primarily use Typescript, and React as our main front-end technologies, interfacing with a Spring Boot back-end and deploying to Kubernetes-based platforms on both private and public cloud. We have a heavy focus on ensuring that our deployments, via a build server, are both efficient and well-controlled.
Job responsibilities
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Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
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Works closely with multiple teams to understand requirements, create solutions which meets business needs for the widest number of teams
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Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
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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.
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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.
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Continuously improves on system stability and efficiency
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Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
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Contributes to software engineering communities of practice and events that explore new and emerging technologies
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Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
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Formal training or certification on software engineering concepts and applied experience
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Hands-on practical experience in system design, application development, testing, and operational stability
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Solid development experience and hands-On coding experience in Java , Micro Services, Spring Boot , Kubernetes , Cloud Computing , Oracle , Kafka
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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.
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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
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Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
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Overall knowledge of the Software Development Life Cycle
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Solid understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security
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Solid experience with Cloud deployment solutions such as Kubernetes
Preferred qualifications, capabilities, and skills
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Advanced competency in Java , Micro Services, Spring Boot , Kubernetes , Cloud Computing , Oracle , Kafka, AWS, Databricks, Data Mesh, Graph QL
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Experience with build tools such as Maven
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Familiarity with modern back-end technologies
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Deep experience in cloud technologies