Description
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Software Engineer at JPMorgan Chase within the AI/ML & Data Platforms team, you are a core technical contributor and are responsible for creating 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 other
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and system
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
- Adds to team culture of diversity, equity, inclusion, and respect
- Provide insightful code reviews and take ownership of outcome
- Heavily uses Python, Snowflake and AWS technologies
- Develop and communicate Product vision that supports the broader organizational vision; ensure team culture consistently demonstrates alignment with leadership principles.
- 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
- Formal training or certification on software engineering concepts and advanced applied experience
- 3+ years of Hands-on practical experience delivering system design, application development, testing, and operational stability
- Fluency in Python
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- In-depth knowledge of the financial services industry and their IT systems
- Practical AWS cloud native experience
- 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.