Python AWS Software Engineer III
Posted 1
view
Summary
Software Engineer III at JPMorganChase's Consumer & Community Banking - Wealth Management team, designing, building, and troubleshooting secure production software in an agile setting. Core stack is Python with database querying, AWS cloud-native services (including Glue), and Databricks/Spark, with use of AI-assisted development tools.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within the Consumer & Community Banking - Wealth Management team, 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. 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.
Job responsibilities
As a Software Engineer III at JPMorganChase within the Consumer & Community Banking - Wealth Management team, 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. 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.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate 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.
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in developing, debugging, and maintaining code in a large corporate environment with Python and database querying languages
- Extensive experience designing and delivering cloud-native solutions on AWS—including compute, storage, security/IAM, networking, and observability—as well as developing AWS Glue jobs.
- Experience building data-intensive applications and workflows using Databricks (Spark, jobs/workflows)
- 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.
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Experience with Airflow
What they ask for
Required
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience developing, debugging, and maintaining code in a large corporate environment with Python and database querying languages
- Extensive experience designing and delivering cloud-native solutions on AWS (compute, storage, security/IAM, networking, observability) and developing AWS Glue jobs
- Experience building data-intensive applications and workflows using Databricks (Spark, jobs/workflows)
- Hands-on experience using enterprise-authorized AI-assisted software development tools with ability to evaluate, validate, and refine AI-generated outputs
- Understanding of responsible AI use in engineering workflows, including data sensitivity and secure handling of inputs/outputs
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred
- Familiarity with modern front-end technologies
- Experience with Airflow