Fullstack Java Software Engineer III

You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.

As a Software Engineer at JPMorganChase within the Commercial & Investment Bank, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, scalable, and observable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system—while also partnering closely with engineering, security, and operations to enable fast, reliable software delivery through modern DevOps practices.

Job responsibilities

• Executes standard software solutions, including design, development, and technical troubleshooting.
• Writes secure and high-quality code using the syntax of at least one programming language with limited guidance.
• Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications.
• Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation.
• Builds, maintains, and improves CI/CD pipelines to standardize build, test, deployment, and release processes.
• Automates infrastructure and environment setup using Infrastructure as Code (IaC) to enable repeatable, reliable provisioning and configuration.
• Standardizes deployment and release practices, including safe rollouts (e.g., phased/canary) and rollbacks, to reduce delivery risk.
• Implements monitoring, logging, alerting, and dashboards to improve observability and operational insight.
• Supports incident response, participates in post-incident reviews, and contributes to remediation and reliability improvements.
• Collaborates closely with developers, security, and operations to embed security and compliance controls into the delivery process (DevSecOps).
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, 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 by automation.

Required qualifications, capabilities, and skills

• 3+ years’ proficient 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 one or more modern programming languages and database querying languages.
• Demonstrable ability to code in one or more languages.
• Experience across the whole Software Development Life Cycle.
• Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security.
• Foundational DevOps capabilities, including working knowledge of CI/CD concepts, environment automation, and release/deployment practices.
• Basic observability understanding (monitoring/logging/alerting) and an interest in improving reliability and operational outcomes.
• Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred qualifications, capabilities, and skills

• Familiarity with modern front-end technologies.
• Exposure to cloud technologies.
• Experience with Infrastructure as Code and configuration automation tooling.
• Experience improving CI/CD pipelines (build/test automation, deployment automation, quality gates).
• Familiarity with operational excellence practices (dashboards, SLO/SLI concepts, incident management, post-incident remediation).