Lead Software Engineer

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 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

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

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.

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

Develop and maintain comprehensive architecture and design documentation for platform services and infrastructure, ensuring compliance with enterprise standards, regulatory requirements, and platform design constraints

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

Proactively identify and address systemic issues, hidden risks, and patterns in data, leveraging insights to enhance coding hygiene, system architecture, and application resiliency

Champion the adoption of emerging technologies and best practices, contributing to internal communities of practice and representing the firm at industry events and forums.

Cultivate a high-performing, diverse engineering team by mentoring, coaching, and promoting a culture of inclusion, respect, and opportunity

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.

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

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.

Expert-level proficiency in Python and/or Java, with extensive experience in developing, debugging, and maintaining complex codebases and database querying languages.

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.

Demonstrated success in deploying and managing enterprise applications using AWS services such as EMR, EKS/ECS, EC2, Event Bus, and S3.

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

Advanced experience in designing and implementing Continuous Integration and Continuous Deployment pipelines using Jenkins, Spinnaker, and related automation tools.

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.

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

Proficient in all aspects of the Software Development Life Cycle

Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security