Develop and support Python and React applications that enable data visualization, dataset sharing, automated code generation, and natural-language application development. Build APIs and web applications using AWS, databases, caching, and search technologies. Collaborate with researchers, analysts, portfolio managers, data scientists, and operations users while applying secure coding, testing, CI/CD, agile practices, and responsible AI-assisted development.
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 JPMorgan Chase within the Asset & Wealth Management Technology 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. Your contributions will be integral to crafting and implementing technical visions that drive our platform forward.
Job responsibilities
- Develop features that allow users to effortlessly load and visualize data using natural language processing, enhancing user interaction and data accessibility.
- Work on automating the generation of Python and Excel code to streamline data retrieval processes, improving efficiency and user experience.
- Create solutions that enable users to register and upload their curated datasets, facilitating data sharing and accessibility through our platform's tools.
- Design and implement features that empower users with minimal Python knowledge to build and deploy applications using natural language prompts, democratizing application development.
- Work closely with researchers, analysts, portfolio managers, data scientists, and operations users to help them successfully build, deploy, and maintain applications on our platforms.
- 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.
- Engage in rapid prototyping, creative problem-solving, and collaborative development, all while working within our existing technology stack and infrastructure.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Strong Python development experience, including application design, debugging, testing, packaging, dependency management, and deployment.
- Strong software engineering fundamentals and hands-on experience developing and supporting modern applications
- Experience building web applications and APIs using modern frameworks and technologies.
- Front-end development experience, ideally with React and TypeScript.
- Familiarity with cloud-native architectures and AWS services such as S3, ECS, Lambda, Athena, and managed database platforms.
- Experience working with databases including PostgreSQL, MongoDB, distributed caching such as Redis, and search technologies such as OpenSearch.
- Understanding of software development best practices including source control, CI/CD, automated testing, code reviews, and agile delivery methods.
- 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.
- Strong verbal and written communication skills, with experience working directly with end users and stakeholders.
Preferred qualifications, capabilities, and skills
- Azure and/or AWS Certifications.
- Experience integrating AI into applications is advantageous
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