Full Stack Engineer - Sr Lead Security Engineer

Join one of the world's most innovative financial institutions, where your engineering skills will help protect and power technology at a global scale. At JPMorganChase, we invest in our people, our platforms, and our future — offering you the opportunity to grow alongside cutting-edge technology and a team that values collaboration, curiosity, and continuous improvement.

As a Sr Lead Security Engineer at JPMorganChase within the Cybersecurity & Technology Controls team in Corporate Technology, you will design and deliver scalable, resilient full-stack solutions that sit at the intersection of security and engineering excellence. You will play a key role in advancing our digital asset custody platform, driving AI-assisted engineering practices, and ensuring our systems are built to the highest standards of reliability and security. This role offers the opportunity to work across a broad technology landscape — from cloud infrastructure to blockchain integrations — while contributing to a team that is shaping the future of secure financial technology.

Job responsibilities

• Design and develop scalable, resilient systems using Java or Python, contributing to continual, iterative improvements for product teams through hands-on software solutions, development, and technical troubleshooting
• Develop and operate microservices including API design, service decomposition, and reliability patterns such as timeouts, retries, idempotency, and dead-letter queues
• Build and maintain integrations using AWS services including API Gateway, SQS, SNS, S3, and RDS; troubleshoot production issues across services and infrastructure
• Produce clear design and architecture artifacts — including service boundaries, data flows, sequence diagrams, and architecture decision records — ensuring implementation aligns with design constraints
• Gather, analyze, and synthesize large, diverse data sets to develop visualizations and reporting that drive continuous improvement of software applications and systems; identify hidden problems and patterns in data to improve coding hygiene and system architecture
• Design and implement components of a digital asset custody platform, including signing pipeline services, policy evaluation engines, and chain adapter integrations across EVM and non-EVM networks
• Architect, deploy, and manage scalable applications using AWS cloud services across the full software development lifecycle
• Drive team adoption of enterprise-authorized AI-assisted engineering practices — including AI-assisted code review, refactoring, test strategy acceleration, and incident root-cause analysis — while establishing consistent validation standards for secure coding, peer review, and automated testing
• Apply knowledge of Software Development Life Cycle toolchain capabilities, including enterprise-authorized AI-assisted development and automation tools, to improve the value realized through automation and delivery speed
• Contribute to software engineering communities of practice and events that explore new and emerging technologies

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience in system design, application development, testing, and operational stability in a large corporate environment using one or more modern programming languages and database querying languages
• Overall knowledge of the Software Development Life Cycle and agile methodologies including CI/CD, application resiliency, and security
• Knowledge of software applications and technical processes within a technical discipline such as cloud, artificial intelligence, machine learning, or mobile
• Experience with digital asset or financial services platforms, including familiarity with transaction lifecycle, key management concepts, or custody workflows
• Experience architecting and building with AWS cloud services
• Demonstrated experience leading effective use of approved AI-assisted software development tools — including coding, code review, test acceleration, and 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 and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Preferred qualifications, capabilities, and skills

• Familiarity with modern front-end technologies
• Experience with blockchain technologies, including public chains such as Ethereum or other EVM-compatible networks
• Experience with advanced CI/CD pipeline design and optimization
• Experience with Terraform scripting and infrastructure-as-code best practices

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