As a Lead Software Engineer at JPMorganChase within the Consumer and Community Banking technology -Deposits Platform, youare 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 firm27s business objectives.

Job responsibilities

• Lead and coordinate end-to-end DR tests and real-time failover events across all applications within the product portfolio, ensuring smooth cross-team collaboration.
• Develop and maintain overarching resiliency frameworks that development and infrastructure teams can consume via automated product offerings and repeatable patterns.
• Define and monitor Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO) for all product components, tracking metrics to identify architectural or procedural gaps.
• Partner with application teams to automate disaster recovery provisioning, scaling, configuration, and monitoring using Infrastructure as Code (IaC) tools like Terraform.
• Drive resiliency testing scenarios and chaos engineering using native tools like AWS Fault Injection Service (FIS) and AWS Resilience Hub to identify vulnerabilities before they impact production
• Partner with SREs to build advanced detection capabilities, leveraging ex-AWS Resilience Hub to assess application resilience and set up proactive CloudWatch alerts.
• Establish, maintain, and execute technical DR playbooks and recovery runbooks, ensuring sequence mapping and dependencies are meticulously documented.
• Mentor and lead software engineers across the organization, promoting continuous learning and operational best practices.
• Collect, govern, and report on DR test artifacts, audit trails, and resilience maturity scores to demonstrate compliance with internal and regulatory standards.
• 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.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Hands-on experience with AWS cloud architectures, specifically DR-enabling services like AWS Elastic Disaster Recovery, AWS Backup, and multi-AZ/multi-region deployments.
• Proficiency in at least one modern language (Python, Go, or Bash) and familiarity with Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
• 5+ years in Site Reliability Engineering (SRE), Disaster Recovery Planning, or Distributed Systems Engineering.

• 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

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

• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience