Software Engineer II Python/Observation

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.