Software Engineer [Multiple Positions Available]

JPMorgan Chase & Co.•Plano, TX

1d•Onsite

About The Position

Duties: Participate in all phases of the Software Development Life Cycle (SDLC), including requirements analysis, system design, coding, testing, and deployment of enterprise-level applications. Analyze technical and business requirements and translate them into application design specifications in alignment with architectural standards. Design, develop, implement, and maintain software application modules; enhance existing modules based on functional requirements. Write and maintain secure, high-quality production code; perform code reviews, debugging, and troubleshooting to ensure application reliability and maintainability. Identify and resolve recurring software and system issues by designing automated remediation and monitoring solutions to improve operational stability. Design and implement cybersecurity solutions focused on identity authentication, fraud detection, and secure data integration with third-party providers. Develop and maintain a real-time risk management platform to support fraud assessment and prevention, incorporating proactive detection mechanisms. Design and automate large-scale data processing pipelines capable of handling multi-terabyte datasets for advanced fraud analytics and risk evaluation. Contribute to the development and operationalization of machine learning models, including building model-serving pipelines to support predictive fraud detection. Deploy, configure, and manage applications on AWS cloud infrastructure, applying Infrastructure as Code (IaC) methodologies to automate provisioning, scaling, and system configuration for high availability and performance.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, Computer Information Systems, or related field of study plus two (2) years of experience in the job offered or as Software Engineer, IT Consultant, or related occupation.
Developing AWS cloud computing services including EKS, S3, IAM, VPC, API Gateway, EMR, and Route53
Managing cloud infrastructure using Terraform to identify and implement common architectural patterns
Leveraging infrastructure as code to automate the provisioning and management of cloud resources
Developing robust backend microservices, REST APIs, and batch jobs using Java 17, Spring Boot, Hibernate and Maven
Deploying APIs via AWS API Gateway
Applying Resilience4j for rate limiting and fault tolerance
Creating clear Swagger API documentation
Working with the full life-cycle of API development of authentication mechanisms including OAuth, X509 Certificate, and ADFS
Python development utilizing on AWS Lambda to develop scalable serverless application and implementing robust testing using PyTest
Comprehensive software testing with JUnit, Mockito, WireMock, Cucumber, Pactflow, JMeter, BlazeMeter, and Gremlin to cover unit, integration, component, contract, and performance testing
Developing and automating large-scale, high- performance data processing systems with Spark and Hadoop for processing and scalable pipelines and leveraging AWS EMR and Glue cloud architectures for data ETL and integration
Deploying software applications with Kubernetes, Docker, Spinnaker, Skaffold, and Jenkins to cover containerization, orchestration, and automating CI/CD pipelines
Messaging frameworks including Kafka, Spring Kafka, and Spring Integration to implement retry mechanisms
Designing and implementing messaging systems to ensure guaranteed message delivery, optimize message exchange efficiency, and support reliable data transformation across distributed applications
Developing and managing modern relational and NoSQL databases, including PostgreSQL and AWS RDS, data model design, data structuring, data manipulation, and query optimization to support scalable and efficient application performance
Implementing and utilizing monitoring and observability tools including Datadog, Grafana, Splunk, CloudWatch, and Dynatrace to ensure system performance, maintain reliability, and enable proactive detection and resolution of operational issues
Designing, developing, and deploying enterprise Java applications using Java 17 and J2EE frameworks on Apache Tomcat, leveraging AWS Cloud Services including EC2 for scalable, secure, and high-availability application hosting and infrastructure management
Leveraging AWS Event Bridge and Step Functions for workflow orchestration and automation
Utilizing JSON and Avro formatted data files/service payloads for data transfer and serialization
Utilizing AI/ML to build and operate model serving pipelines for a portfolio of AI projects and machine learning frameworks and libraries to operationalize machine learning models for improved fraud prediction and risk management
Implementing and integrating Single Sign-On (SSO) solutions to streamline user authentication across enterprise applications, enhancing security, user experience, and centralized access control
Conducting automated, regression, system integration, unit, and user acceptance testing (UAT) to ensure application functionality, performance, and reliability across development cycles
Utilizing Git for source control, version management, and collaborative code development in distributed team environments
Developing and managing configuration and data exchange using XML and YAML for structured communication between services and environments
Creating, managing, and validating configuration files and data structures using XML and YAML to support application setup, service communication, and environment configuration

Responsibilities

Participate in all phases of the Software Development Life Cycle (SDLC)
Analyze technical and business requirements and translate them into application design specifications
Design, develop, implement, and maintain software application modules
Write and maintain secure, high-quality production code
Identify and resolve recurring software and system issues
Design and implement cybersecurity solutions
Develop and maintain a real-time risk management platform
Design and automate large-scale data processing pipelines
Contribute to the development and operationalization of machine learning models
Deploy, configure, and manage applications on AWS cloud infrastructure