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# Software Engineer [Multiple Positions Available]

- **Company:** JPMorgan Chase & Co.
- **Location:** Wilmington, DE, United States
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Build Automation, Microsoft Azure, Continuous Integration, DevOps, Distributed Systems, Amazon DynamoDB, Gradle, Monitoring of Systems, Identity and Access Management, Information Systems Security Architecture Professional, Spring Framework, Python (Programming Language), Apache Maven, MySQL, NoSQL, Object-Oriented Software Development, Software Engineering, Software Systems, SQL Databases, Systems Integration, AI Infrastructure, Data Processing, Google Cloud, Pytorch, System Availability, Spring-boot, Multi-Cloud, AWS Lambda, Kubernetes, Information Technology, Deployment Automation, HuggingFace, Data Management, Machine Learning Operations, Functional Programming, Restful APIs, Serverless Computing, AWS EKS, Docker, Microservices
- **Published:** August 20, 2026
- **Apply:** https://www.jobmonkeyjobs.com/career/27948536/Software-Engineer-Multiple-Positions-Available-Delaware-Wilmington-7463

## About the Role

Minimum education and experience required: Master's degree in Computer Science or related field of study plus 3 years of experience in the job offered or as Software Engineer, Programmer Analyst, or related occupation. The employer will alternatively accept a Bachelor's degree in Computer Science or related field of study plus 5 years of experience in the job offered or as Software Engineer, Programmer Analyst, or related occupation.

Skills Required: This position requires experience with the following: Architecting and implementing robust microservices leveraging engineering practices, AWS Cloud, AWS EKS (Kubernetes), Python, and Java to deliver scalable and maintainable solutions for complex business requirements; Performing sophisticated data manipulation, structuring, and flow design, optimizing queries for both SQL and NoSQL databases including Aurora MySQL and AWS DynamoDB to ensure reliable, and high-performance data interactions; Engineering enterprise-grade software solutions using Spring, Spring Boot, and build automation tools including Maven and Gradle to manage application dependencies and streamline the development lifecycle; Designing and developing serverless applications on AWS Cloud utilizing AWS Lambda, S3, Security Groups, VPCs, IAM, EC2, EKS, RDS, and DynamoDB to achieve secure architectures; Leading the design and implementation of AI model evaluation workflows, utilizing PyTorch and HuggingFace
Transformers, containerizing solutions with Docker, and orchestrating deployments on Kubernetes for scalable and reproducible machine learning operations; Developing and deploying microservices-based applications as RESTful APIs to ensure seamless integration, high availability, and optimal performance in distributed environments; Building and delivering highly scalable, performant applications across multi-cloud environments including AWS, GCP, and Azure, leveraging AWS, GCP and Azure technologies and best practices for global reach and reliability; and Creating and deploying AI agents to modernize AI infrastructure and APIs to drive innovation and operational efficiency in next-generation intelligent systems.

## Description

Duties: Design, develop, and implement software solutions to address complex business challenges, applying modern engineering practices throughout the software development lifecycle. Architect and deploy scalable microservices and enterprise-grade applications using both object-oriented and functional programming languages, leveraging cloud platforms for reliability and performance. Collaborate with cross-functional teams to deliver system enhancements, automate processes, and optimize platform operations, utilizing infrastructure-as-code and cloud-native orchestration technologies for efficient cloud resource management. Develop and maintain RESTful APIs and exception handling frameworks to enhance platform extensibility and reliability, integrating both SQL and NoSQL database solutions for data management. Lead the design and implementation of secure, serverless architectures and containerized machine learning workflows, employing cloud-native services and Kubernetes for scalable
operations. Build and automate deployment pipelines, monitoring tools, and access controls to ensure secure, compliant environments and seamless integration of new technologies. Implement DevOps methodologies, including automated deployment, monitoring, and continuous integration, to enhance development workflows and drive ongoing operational improvements.


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