Software Engineer III - AWM Technology

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 organization, 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.

As a Software Engineer III within Asset Management's Sales Experience Platform (SEP) Team, you will play a critical role in designing, developing, and maintaining large-scale data integration solutions that support complex enterprise environments. You will leverage your hands-on expertise in production-grade Python, microservices, APIs, and AWS cloud technologies to deliver scalable, secure, and high-performance software solutions. This role offers the opportunity to work on cutting-edge financial technology projects that drive business value and innovation in asset management.

• Design, develop, and implement large-scale data integration solutions across complex enterprise systems to support asset management business needs.
• Build and maintain production-grade Python applications with a focus on reliability, scalability, and performance.
• Develop and consume microservices and APIs to enable seamless data flow and system interoperability.
• Utilize AWS cloud services to architect, deploy, and manage cloud-native applications and infrastructure.
• Collaborate with cross-functional teams including product owners, data architects, and business analysts to translate requirements into technical solutions.
• Participate in code reviews, testing, and continuous integration/continuous deployment (CI/CD) pipelines to ensure high-quality software delivery.
• Troubleshoot and resolve production issues, ensuring minimal downtime and optimal system performance.
• Contribute to the design and evolution of data models to support efficient data storage, retrieval, and processing.
• Engage in knowledge sharing and mentoring of junior engineers to foster a collaborative engineering culture.
• 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.

• 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 (Python, Type Script and/or Jave)) and database querying languages
• Proven experience with large-scale data integrations in complex enterprise environments.
• Expertise in designing, building, and consuming microservices and RESTful APIs.
• Solid experience with AWS cloud services including but not limited to EC2, Lambda, S3, API Gateway, Glue and Cloud Formation.
• 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 and best practices including version control, automated testing, and CI/CD.
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security