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# Java / AWS Lead Software Engineer

- **Company:** JPMorgan Chase & Co.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Software Applications, Automation of Tests, Cloud Computing, Software Quality, Code Review, Continuous Delivery, Continuous Integration, Relational Databases, Database Design, DevOps, Spring Framework, PostgreSQL, Oracle (Applications), Performance Tuning, Query Optimization, Software Tools, Standard Sql, Secure Coding, Software Engineering, Software Systems, Strategies of Testing, Toolchain, Software Organization, Spring-boot, Cloudformation, Kubernetes, Infrastructure Automation Frameworks, Production Code, Front End Software Development, Amazon Simple Queue Service (SQS), Terraform, Code Restructuring
- **Published:** July 22, 2026
- **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210763443

## About the Role

* 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
 * Strong experience with Java, AWS, Spring Boot, and Terraform
 * Proficiency in Java, with working knowledge of SQL and a strong understanding of software development best practices
 * Extensive hands-on experience with relational databases, particularly Oracle and PostgreSQL, including database design, query optimization, and performance tuning
 * Proficiency in automation and continuous delivery methods
 * Hands-on experience with AWS services, including EC2, Lambda, KMS, ECS, EKS, S3, EMR, Athena, SQS, and EventBridge
 * Hands-on experience with cloud infrastructure provisioning tools such as Terraform and AWS CloudFormation
 * 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

Preferred qualifications, capabilities, and skills

 * Familiarity with modern front-end technologies
 * Certifications in target areas (Cloud/Kubernetes/IaC etc.)
 * Understanding of payments processing within a banking environment

## Description

* Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
 * Develops secure and high-quality production code, and reviews and debugs code written by others
 * Designs and implements scalable, resilient, high-performance solutions using Java, Spring, AWS, Oracle, and PostgreSQL
 * Leads incident response and root cause analysis for critical production issues, driving preventive actions and continuous improvement
 * Manages and optimizes cloud infrastructure with a focus on cost efficiency, security, compliance, and operational resilience
 * Drives adoption of DevOps practices, including CI/CD, infrastructure as code, automated testing, and reliable deployment patterns
 * Evaluates emerging technologies and tools, recommending adoption where they improve team productivity, product capability, or platform reliability
 * 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.
 * Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
 * Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture


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