You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.
As a Software Engineer II at JPMorgan Chase within the Corporate Technology, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
Job responsibilities
Executes standard software solutions, design, development, and technical troubleshootingDevelop, test, and debug automated tasks (Apps, Systems, Infrastructure)Troubleshoot priority incidents, facilitate blameless post-mortems.Work with development teams throughout the software life cycle ensuring sustainable software releases.Perform analytics on previous incidents and usage patterns to better predict issues and take proactive actions.Build automations to reduce manual interventions for production operations.Build real-time monitoring and observability tools and processes.Build and drive adoption for greater self-healing and resiliency patterns.Lead and participate in performance tests; identify bottlenecks, opportunities for optimization, and capacity demands.Participate in the 24x7 support coverage as needed.Applies technical troubleshooting to break down solutions and solve technical problems of basic complexity
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 2+ years applied experienceStrong development skills in Java, Python, or Scala.Experience with the Spring framework (Core, REST API, web services, messaging), with experience in Spring Boot and microservice architecture.Experience with data storage solutions, including SQL, NoSQL databases (Cassandra ), data lakes, and S3.Familiarity with logging and monitoring tools such as Kibana, Splunk, Elastic Search, Dynatrace, AppDynamics, Grafana, CloudWatch, and Datadog.Experience with Continuous Integration & Continuous Deployment processes using tools like Jenkins and Spinnaker.Ability to deploy, scale, and manage ML models in production environments, optimizing for performance and cost-efficiency.Strong analytical and troubleshooting skills, with the ability to diagnose and resolve issues in ML pipelines and production systems.Excellent communication skills, with the ability to collaborate effectively with data scientists, engineers, and other stakeholders, and a willingness to stay updated with the latest trends in ML and MLOps.
Preferred qualifications, capabilities, and skills
Relevant certifications in cloud platforms (e.g., AWS Machine Learning, DevOps, Certified Kubernetes Administrator/Developer).Experience in building and supporting ML applications. Experience working with AWS services.