Software Engineer [multiple Positions Available]

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Asset & Wealth Management

Software Engineer role focused on designing, developing, and implementing software solutions, with a significant emphasis on integrating Artificial Intelligence (AI) and Machine Learning (ML) models into applications to enhance automation, data analysis, and predictive capabilities. The role involves developing large-scale ML systems and utilizing Python for application development, supporting business objectives with ML algorithms and LLMs. Experience with core Java, various UI frameworks, web services, cloud environments (AWS, PCF), and CI/CD practices is required.

What you'd actually do

  1. Design, develop and implement software solutions.
  2. Solve business problems through innovation and engineering practices.
  3. Involved in all aspects of the Software Development Lifecycle (SDLC) including analyzing requirements, incorporating architectural standards into application design specifications, documenting application specifications, translating technical requirements into programmed application modules, and developing or enhancing software application modules.
  4. Identify or troubleshoot application code-related issues.
  5. Take active role in code reviews to ensure solutions are aligned to pre-defined architectural specifications.

Skills

Required

  • Core Java
  • Java 17
  • J2EE
  • Hibernate
  • Spring MVC
  • Java Server Faces (JSF)
  • Angular (including Angular 15)
  • ReactJS
  • NodeJS
  • Form.io
  • SOAP and RESTful web services
  • microservices development using Spring Boot
  • RESTful APIs
  • Integrating Artificial Intelligence (AI) and Machine Learning (ML) models into applications
  • implementing machine learning algorithms
  • Large Language Models (LLMs)
  • Python for application development
  • Streamlit
  • Flask
  • Django
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Scikit-learn
  • TensorFlow
  • SDL Tridion
  • Developing dynamic forms and applications using Form.io
  • Developing and maintaining scalable applications
  • Amazon Web Services (AWS)
  • Pivotal Cloud Foundry
  • orchestration
  • containerized applications
  • Spring framework components
  • Model View Controller (MVC)
  • Spring JDBC
  • Spring Data JPA
  • Spring Batch
  • Spring Security
  • Spring Cloud API Gateway
  • Business Process Model and Notation (BPMN)
  • Java concurrency
  • concurrency patterns
  • thread-safe code
  • GIT
  • Bitbucket
  • Apache Kafka
  • MQ
  • SQL
  • No-SQL
  • caching platforms
  • Agile SDLC
  • Application Architecture Disciplines
  • Continuous Integration and Continuous Deployment (CI/CD)
  • Application Resiliency
  • Security
  • automated tooling
  • UTC
  • automation using Java
  • Selenium
  • Cucumber
  • Behavior Driven Development (BDD)
  • Java
  • Selenium
  • Cucumber
  • Behavior Driven Development (BDD)
  • JUnit
  • Jasmine
  • Mockito
  • automated QA tools
  • performance monitoring
  • observability tools
  • Dynatrace
  • Kibana
  • JMeter
  • Splunk
  • Newrelic
  • Grafana

What the JD emphasized

  • Integrating Artificial Intelligence (AI) and Machine Learning (ML) models into applications
  • Implementing machine learning algorithms and Large Language Models (LLMs)
  • Developing large-scale Machine Learning systems

Other signals

  • Integrating AI/ML models into applications
  • Implementing machine learning algorithms and LLMs
  • Developing large-scale Machine Learning systems