Software Engineer II- Python

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer II at JPMorgan Chase within Consumer and Community Banking, 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.

Executes standard software solution, design, development, and technical troubleshooting Writes secure and high-quality code using the syntax of at least one programming language with limited guidance Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards. 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, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development Build and operate on AWS using services such as S3, RDS, Lambda, Redshift, Athena, Step Functions, MSK, ECS, RDS and EKS architectures. Operate as a Python-first engineer with Java skillset —able to read, debug, maintain, and enhance Java-based services and integrations supporting the platform. Required Qualifications, Capabilities, and Skills Formal training or certification on software engineering concepts and 2+ years applied experience Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs. Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations. Strong Python skills for AI/data processing and production engineering (performance, reliability, testing, and maintainability). Proficiency with GenAI models (e.g., OpenAI) to solve business problems. Experience with LLM orchestration , AI usage patterns, agentic frameworks, and MCP servers . Strong problem-solving and troubleshooting skills, clear stakeholder communication, rapid POC-to-production execution, and mentoring/coaching ability. Preferred Qualifications, Capabilities, and Skills Proficiency in all other AWS components—preferably AWS certified. Experience integrating AI/ML models into data pipelines is a plus. Experience with version control (Git) and CI/CD pipelines.