Software Engineer III - AWM Technology
Listed on 2026-10-15
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Software Development
Software Engineer, Backend Developer, Cloud Engineer - Software, DevOps
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.
Job ResponsibilitiesDesign, 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
Experience…
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