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 & Community Banking Digital Cloud 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
• 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.
• 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
• Design and develop a scalable ML platform to support model training, deployment, and monitoring
• Build and maintain infrastructure for automated ML pipelines, ensuring reliability and reproducibility supporting different model frameworks and architectures
• Set up monitoring and reliability for both infrastructure and models utilizing Prometheus and Grafana
• Code infrastructure with Terraform and utilizing Python for automation
• Perform DevOps in Kubernetes (K8s), Docker, Helm, GitOps, and CI/CD pipelines (Jenkins, GitLab CI) Required qualifications, capabilities, and skills
• Formal training or certification on software engineering concepts and 5+ years applied experience
• 8+ years of hands-on software/platform engineering experience, including leading cloud-native delivery for business-critical systems.
• Expert Infrastructure as Code with Terraform (modules, state backends, workspaces, CI integration, policy contr.

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