JOB DESCRIPTIONWe 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
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Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
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Oversee the end-to-end design, development, and deployment of scalable and resilient platform solutions, setting technical direction and standards to ensure secure infrastructure that aligns with organizational objectives and industry best practices.
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Lead cross-functional teams in building secure, high-quality platform components and automation, fostering a culture of technical excellence, innovation, and continuous improvement across engineering disciplines
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Develop and maintain comprehensive architecture and design documentation for platform services and infrastructure, ensuring compliance with enterprise standards, regulatory requirements, and platform design constraints
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Direct the analysis and synthesis of large, diverse data sets to generate actionable insights, visualizations, and reporting that inform strategic decision-making and drive operational excellence
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Proactively identify and address systemic issues, hidden risks, and patterns in data, leveraging insights to enhance coding hygiene, system architecture, and application resiliency
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Champion the adoption of emerging technologies and best practices, contributing to internal communities of practice and representing the firm at industry events and forums.
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Cultivate a high-performing, diverse engineering team by mentoring, coaching, and promoting a culture of inclusion, respect, and opportunity
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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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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
Required qualifications, capabilities, and skills
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Formal training or certification on software engineering concepts and 5+ years applied experience in system architecture, application development, testing, and operational stability within large-scale, enterprise environments.
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Expert-level proficiency in Python and/or Java, with extensive experience in developing, debugging, and maintaining complex codebases and database querying languages.
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Deep expertise in SQL and NoSQL databases, data lakes, and AWS S3, with a proven ability to architect and implement scalable, secure data storage solutions.
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Demonstrated success in deploying and managing enterprise applications using AWS services such as EMR, EKS/ECS, EC2, Event Bus, and S3.
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Mastery of enterprise monitoring and logging tools, including Splunk, Elastic Search, Dynatrace, AppDynamics, Grafana, CloudWatch, and Datadog, with a focus on proactive system health and performance management
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Advanced experience in designing and implementing Continuous Integration and Continuous Deployment pipelines using Jenkins, Spinnaker, and related automation tools.
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In-depth understanding of the full software development lifecycle, agile methodologies, application resiliency, and security principles, with a track record of delivering secure, reliable solutions.
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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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Proficient in all aspects of the Software Development Life Cycle
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Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
