Lead Software Engineer - Python Full stack developer

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As a Lead Software Engineer at JPMorgan Chase within the Infrastructure Platforms - Networks, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
Leads the technical design of features, translating business requirements into scalable, secure, and maintainable solutions while defining architecture, interfaces, and implementation approaches.
Provides technical leadership to the engineering team by guiding implementation, reviewing designs and code, resolving technical blockers, and ensuring high-quality delivery aligned with engineering standards.
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
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
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.
Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
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 5+ years applied experience
Proficient experience in Python, with hands-on expertise in Django or Flask or FastAPI.
Experience with React and AngularJS
Knowledge on Astronomer/Airflow. Strong knowledge of API development.
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs
Solid understanding of agile methodologies, application resiliency, and system integration.
Knowledge of code maintainability, including source control (Bitbucket or similar), code branching strategies, and deployment in cloud environments.
Hands-on practical experience delivering system design, application development, testing, and operational stability
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong 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 coaching engineers on safe, compliant adoption within delivery practices
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
Good knowledge of networking concepts, a basic CCNA certification
Experience with cloud-based technologies, knowledge of Kubernetes , Dockers