Sr Lead Software Engineer Devops & Infra

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 JPMorgan Chase within the Consumer & Community Banking 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

• 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 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