We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Software Engineer II at JPMorgan Chase in the Consumer and Community Banking Risk team, you will establish and implement robust engineering practices. Your role involves integrating software and systems to solve operational challenges, enhancing system performance, developing infrastructure, and automating processes to reduce workload. You will manage mission-critical real-time applications in a production environment, collaborating with a diverse team to encourage innovative thinking and deliver high-quality solutions that meet business objectives.

Job responsibilities

Develop, 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.

Required qualifications, capabilities, and skills

Formal training or certification in software engineering concepts and 2+ years of applied experience.Strong development skills in Java, Python, or Scala.Knowledge of data preprocessing, ETL processes, and data pipeline creation.Experience with data storage solutions, including SQL, NoSQL databases (Cassandra ), data lakes, and S3.Proficiency in using cloud services like AWS EMR, EKS, EC2, and S3 for deploying and managing ML models.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, DevOps, Certified Kubernetes Administrator).