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 JPMorganChase within the AI/ML Data Platforms, 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 solution, design, development, and technical troubleshooting • Writes secure and high-quality code using the syntax of at least one programming language with limited guidance • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards. • Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation • Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity • Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development • Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems Required qualifications, capabilities, and skills • Formal training or certification on software engineering concepts and 2+ years applied experience Hands-on practical experience in system design, application development, testing, and operational stability • Experience in Python developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages • Experience in observability such as white and black box monitoring, service level objective alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, and others • Strong understanding of SLI/SLO/SLA and Error Budgets • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations. • Experience across the whole Software Development Life Cycle • Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security Preferred qualifications, capabilities, and skills • Experience in Data pipelines using Spark • Exposure to AWS & Databricks Platform administration. • Knowledge of containerization (Docker, Kubernetes) and orchestration.