Software Engineer III - Data Platform/AI Engineer (Python/AWS)

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.