Job Description
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.
Job Responsibilities
- 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.
