Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorganChase within the Payments Trust and Safety Technology group, 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. You will be part of the Fraud Protection group, building solutions for merchants to protect themselves against fraudulent behavior. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

• Executes creative software solutions, design, development, and deploy cloud-native applications using AWS services (EC2, S3, Lambda, RDS, Aurora, ECS, EKS, etc.)
• Automate infrastructure provisioning and application deployment using AWS tools (CloudFormation, Terraform, AWS CDK)
• 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 system
• Monitor, troubleshoot, and optimize application performance and reliability in the AWS environment
• Ensure security and compliance by implementing IAM policies, encryption, and monitoring
• Document technical solutions and provide support for audits and regulatory reviews
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge cloud technologies
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale
• Deliver high-quality results within tight deadlines while maintaining a strong focus on code optimization, performance tuning, and engineering best practices

Required qualifications, capabilities, and skills

• Formal training or certification on Software Engineering concepts and 5+ years applied experience
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls
• Extensive hands-on experience with AWS cloud services and infrastructure
• Experience with S3, Aurora Postgres, ECS, EKS, RDS, Lambda, Glue, ALB/NLB and serverless architectures
• Proficiency in programming languages (Java, Spring boot, Python, Node.js, etc.)
• Proficiency in automation, continuous delivery methods and all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security and working with Kafka for event Streaming
• In-depth knowledge of the financial services industry and their IT systems
• Experienced with pair programming agents such as GitHub Copilot to accelerate prototyping
• Proven experience in building high-volume, low-latency, high-throughput transactional systems

• Full stack development knowledge with strong enterprise architecture design concepts to allow for unified user experience leveraging data sharing capabilities with API, Kafka
• Case management workflow and orchestration to serve as the backbone of a unified user experience across multiple cross-functional teams
• Vibe coding experience and conceptual knowledge while leveraging developer assistant tools like GitHub Copilot to allow for efficiency gains