Lead Software Engineer

As a Lead Software Engineer at JPMorganChase within the Infrastructure Platforms, 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. J ob responsibilities Executes creative software solutions, design, development, and technical troubleshooting with the 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 Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Drives team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident and 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 . Adds to team culture of diversity, opportunity, inclusion, and respect Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience Advanced proficiency in one or more programming language(s) and framework(s) (e.g., Python, Django, Java, etc.) Proficiency in automation and continuous delivery methods, and hands-on practical experience delivering system design, application development, testing, and operational stability Proficient in all aspects of the Software Development Life Cycle, with an advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Working knowledge of SDLC toolchains and proven experience applying enterprise-authorized AI-assisted development and automation capabilities to increase the value realized from automation (e.g., improved efficiency, reliability, maintainability, and measurable throughput/quality outcomes). Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Demonstrated ability to drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, accelerated test strategy, incident and root-cause analysis support), while establishing and enforcing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. Proven expertise in designing, deploying, and managing containerized distributed applications, with a strong understanding of orchestration and scaling strategies Hands-on experience with AWS Infrastructure as a Service (IaaS), including provisioning and operating core compute, storage, and networking services (e.g., EC2, EBS, S3, VPC) Demonstrated ability to architect and manage infrastructure on AWS Cloud, utilizing Infrastructure as Code (IaC) tools like Terraform to automate and optimize deployment processes Proven experience in designing and implementing control plane architectures for large-scale applications, focusing on efficient resource management, orchestration, and system reliability to support complex, distributed systems In-depth knowledge of the financial services industry and their IT systems Preferred qualifications, capabilities, and skills Hands-on experience with relational databases, particularly CockroachDB or similar distributed databases, ensuring data consistency, reliability, and performance in distributed environments Practical cloud native experience