Lead Software Engineer – Cloud AWS Resiliency

We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.

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 firms 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