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

As a Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking, 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.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with 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
• Implement infrastructure as code (IaC) using AWS CloudFormation, Terraform, or AWS CDK.
• Develop and maintain CI/CD pipelines using Jenkins, GitLab CI, AWS CodePipeline, or similar tools.
• Automate build, test, and deployment processes for rapid and reliable application delivery.
• Write and maintain scripts for automating cloud infrastructure and application deployment (Python, Bash, PowerShell).
• Implement configuration management with tools like Ansible, Chef, or Puppet.
• Set up and manage monitoring, logging, and alerting systems (AWS CloudWatch, ELK Stack, Prometheus).
• Implement and enforce security best practices and compliance requirements in cloud environments and pipelines.
• 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.

Required qualifications, capabilities, and skills

• Formal training or certification in software engineering concepts and 5+ years of applied experience
• Experience with AWS services including EKS, EC2, ALB, NLB, S3, RDS, Lambda, VPC, IAM, and CloudFormation.
• Experience with CI/CD tools and delivery practices.
• Experience with scripting and automation.
• Proficiency in one or more programming/scripting languages (e.g., Python, Java, Node.js, Bash, PowerShell).
• Experience with IaC tools such as CloudFormation, Terraform, or AWS CDK.
• Familiarity with Docker and Kubernetes.
• Experience with monitoring and logging tools such as AWS CloudWatch, ELK Stack, or Prometheus.
• Hands-on experience with system design, application development, testing, and operational support.
• 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.

• AWS Certified DevOps Engineer, AWS Certified Solutions Architect, or similar certifications.
• Experience with additional CI/CD tools such as Spinnaker.
• Experience in highly regulated environments or with compliance frameworks.
• Proficient in all aspects of the Software Development Life Cycle
• 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.)
• Practical cloud native experience