AWS Lead Software Engineer-Full Stack/Java/SpringBoot

JPMorgan Chase & Co.; Tampa (FL); Vor Ort; USD 120.000 - 190.000; Vollzeit

Zusammenfassung

JPMorgan Chase & Co. is seeking an AWS Lead Software Engineer-Full Stack/Java/SpringBoot in Tampa, FL, to contribute as a core technical member of the Payments Technology team.

You will design, build, and deliver secure, scalable software solutions across multiple business functions within a healthcare technology context, operating within an agile framework. The role emphasizes production-grade code, architecture reviews, and leadership in communities of practice, with a focus on responsible AI

Qualifikationen

• Formal training or certification on Software Engineering concepts and 5+ years applied experience.
• Hands-on experience coding in Java, Spring Boot, JPA, SQL, REST.
• Experience with event driven architecture using Kafka.
• Experience building RESTful backend applications using Spring Boot and solid relational enterprise databases with Oracle.
• Experience with version control systems, such as Git.
• Strong knowledge of CI/CD e.g. Jenkins.
• Hands-on practical experience in system design, application development, testing and operational stability.

Aufgaben

• Executes creative software solutions, design, development, and technical troubleshooting.
• Develops secure high-quality production code, and reviews and debugs code written by others.
• Identifies opportunities to automate remediation to improve stability.
• Leads evaluation sessions with external vendors and internal teams on architecture designs.
• Leads communities of practice across Software Engineering for new technologies.
• Drives team adoption of AI-assisted engineering practices to improve code quality and delivery speed.
• Applies knowledge of SDLC tools and AI-assisted development capabilities to enhance automation.
• Contributes to a culture of diversity, inclusion, and respect.

Kenntnisse

Java

Spring Boot

REST API design

SQL

System design

AI-assisted development awareness

Security best practices

Operational stability

Agile teamwork leadership

Ausbildung

Software Engineering Certification

Tools

Kafka

Git

Jenkins

Kubernetes

Docker

Gradle

Groovy

Python

Jobbeschreibung

Be an integral part of an agile team that’s constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As an AWS Lead Software Engineer-Full Stack/Java/SpringBoot at JPMorgan Chase within Commercial and Investment Banking's Payments Technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading healthcare technology product 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
• 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
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• 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
• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on Software Engineering concepts and 5+ years applied experience
• Hands-on experience coding in Java, Spring Boot, JPA, SQL, REST
• Experience with event driven architecture using Kafka
• Experience building RESTful backend applications using Spring Boot and solid relational enterprise databases with Oracle
• Experience with version control systems, such as Git.
• Strong knowledge of CI/CD e.g. Jenkins
• Hands-on practical experience in system design, application development, testing and operational stability
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• 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
• Solid understanding of cross cutting concerns such as Application Resiliency, and Security

Preferred qualifications, capabilities, and skills

• Familiarity with Groovy and Gradle
• Experience coding in Python
• Strong understanding of containerization technologies such as Kubernetes or Docker
• Exposure to AI/ML technologies – especially familiarity with model training and inference
• Exposure to AWS cloud technologies