Software Engineer III - Java/AWS/Kubernetes

JPMorgan Chase; Tampa (FL); On-site; USD 110,000 - 140,000; Full time

Job summary

JPMorganChase, Tampa, is seeking a Software Engineer III to design and deliver trusted market-leading technology products in a secure, scalable way. You will contribute to the Payments Common Core Services team, building production-ready code and maintaining robust systems.

The role requires hands-on experience with Java, Spring Boot, microservices, REST APIs, and databases, plus familiarity with enterprise AI-assisted development tools to improve coding quality and velocity in a large corporate

Qualifications

• Formal training or certification on software engineering concepts.

Responsibilities

• Executes software solutions, design, development, and troubleshooting with ability to tackle non-routine problems.

Skills

Java

Spring Boot

Microservices

REST API development

AI-assisted development tools

Jenkins CI/CD

AWS fundamentals

Software Development Life Cycle

Distributed databases

Tools

AWS

Kubernetes

Docker

Terraform

Jenkins

Job description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III - Java/AWS at JPMorganChase within the Payments Common Core Services team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems.
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables, including code generation/refactoring, unit test creation, and documentation, while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• 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 through automation.
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development.
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems.
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years of applied experience.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Experience developing, debugging, and maintaining code in a large corporate environment with Java, Spring Boot, Microservices, REST API development, and one or more database querying languages.
• Hands-on experience using enterprise-authorized AI-assisted software development tools.
• Understanding of responsible AI use in engineering workflows, including the ability to guide peers.
• Experience with distributed databases and Jenkins CI/CD pipelines
• Overall knowledge of the Software Development Life Cycle.

Preferred qualifications, capabilities, and skills

• Exposure to AWS cloud technologies such as EC2, EKS, RDS, S3, or Lambda.
• Practical experience using AI-assisted developer tools and AI agents (e.g., Copilot, Claude Code, or equivalent) to improve engineering productivity, code quality, and knowledge acquisition.
• Kubernetes and infrastructure-as-code experience such as Kubernetes, Terraform
• Containerization experience such as Docker images/containers