at J.P. Morgan
Bulge Bracket Investment BanksPosted 13 days ago
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**Software Engineer III (Java/AWS) | JPMorgan Chase, Consumer Banking, NY** Highly experienced Software Engineer III role, crafting secure, high-quality Java code for enterprise-level systems. Key responsibilities include: - Designing and implementing complex applications, troubleshooting with innovative problem-solving skills. - Leveraging AI coding assist tools to enhance code quality, peer reviewing and automating tests. - Developing architecture, visualizations, and reports from large datasets for continuous improvement. - Proactively identifying hidden data patterns and driving coding hygiene and system architecture enhancements. Candidates must possess a formal software engineering background and 3+ years of practical experience, plus: - Proven Java/AWS expertise, hands-on experience with Kafka, Cassandra, and Hadoop. - Experience in middle-tier/backend systems development in Java/Linux and understanding of AI ethics in engineering.
- Compensation
- Not specified
- City
- New York City
- Country
- United States
Currency: Not specified
Full Job Description
Location: NY, United States
As a Software Engineer III at JPMorganChase within the Consumer Banking division, 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 firms 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
- 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 one or more modern programming languages and database querying languages
- Experience with Python, AWS
- Experience with Real time messaging Kafka / Java on Gaia Application Platform
- 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.
- Experience with ODS Cassandra
- Experience in middle-tier/backend systems development in Java/Linux
- Working experience with Hadoop, Enterprise Java development, NoSQL data platforms (Cassandra)
- 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
- Exposure to Machine Learning
- Experience with PySpark
- Working experience with Pub/sub messaging (Rendezvous, AMPS, Kafka, etc.), Stream processing (Storm, Hbase, Nifi, Spark Streaming, etc.)
