Design, develop, and maintain secure, scalable production software. Produce architecture artifacts, troubleshoot complex systems, analyze large datasets for improvements, leverage AI-assisted development tools, and contribute to engineering communities and best practices.
Join a team where your software engineering expertise drives impactful solutions and career growth. Be part of a collaborative environment that values innovation and technical excellence.
As a Software Engineer III at JPMorgan Chase within the Chief Technology Office team, you 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. You will work in a collaborative environment that encourages continuous learning and growth. You will help shape the future of technology at JPMorgan Chase.
Job responsibilities
- Execute software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Create secure and high-quality production code and maintain algorithms that run synchronously with appropriate systems
- Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- 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.
- Proactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture
- Contribute to software engineering communities of practice and events that explore new and emerging technologies
Required qualifications, capabilities and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficient in coding in one or more languages
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Experience with JFrog Artifactory and package management tools (Maven, Gradle, NPM, Pypi, NuGet, Docker, RUST)
- Expertise in AWS (EKS, ECS, Lambda, MongoDB, PostgreSQL, DynamoDB, API Gateway, RDS), Kubernetes, Java/Spring Boot, REST API, GraphQL, Go Lang
- 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.
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Preferred qualifications, capabilities and skills
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
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